代写美国留学生计算机硕士论文-留学生硕士毕业论文范文-网络技术与网络优化模式探究- network technology

代写美国留学生计算机硕士论文,留学生硕士毕业论文范文， 写手您好，非常感谢您的配合和辛苦劳动，很不错。但是还有一些小问题，请看目录和文章的细节，我已经红色标出来了。另外，参考文献还是有一点问题，文章中的参考文献都只写姓氏就行了，可是我发现有些文章中的参考文献还是很长的一个名字，我也不知道哪个是姓氏， 也不好乱改，所以请写手再好好检查一下。最后就是只要是有任何引用的地方，都请写手一定要标出来，只要标出来，就算有一点点问题，也可以解释，但是不标出来，就没得商量了，所以很严重。有的如果真的实在是没有办法找到来源，那就只能编一个参考文献了，总之就是比没有强。参考文献也是越多越好。非常感谢

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STATEMENT 1
This work is the result of my own investigations, except where otherwise stated. Where correction services have been used, the extent and nature of the correction are clearly marked in a footnote(s).
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Acknowledgements
First and foremost, I would love to show my great gratitude to my tutor Dr. Jonathan Gosling who is a strict and well-read professor. I get a lot of progress and improving by his helping in life and guiding me in learning. It is hard to describe my gratitude by words. He is both my tutor in study and helpful friend in life. Instructor meticulous work, dedicated professionalism sets a good example to me. From dissertations to research work carried out at each step, all have devoted their attention and teach, they raised a lot of very useful and valuable suggestions, so I was able to smoothly complete the task of studying and writing papers.

I thank my dear classmates and friends, because of your accompanying, let my life has been bereft of entertainment, so my research has been the object of discussion, let me talk to you when I am being in troubles or bad mood. Thanks to your care and help me in every possible way, I could successfully complete the paper. Finally would like to thank my family, quietly in the background gives me great concern and support. My success is also your one. Thank you all for giving me support and love, I will be more efforts and hard working in the future.           

Abstract
In the 1950s United States researchers firstly used network technology, in the 1960s Professor Hua introduced the technology over to China. The network technology has been rapidly applied to project management and other fields. Network optimization technology is a high-level network planning, and also it is an important part of research fields in project management. Network optimization contains four different sides, which are fixed duration-resources balance, resources limited-shortest duration, duration-coat exchanged and maximizing the net present value of projects, and the last side in present years has become a focus in network optimization. Based on the fore-researcher’s achievement, some research has been done in this paper on the problem of evaluating and maximizing the net present value of project, activity’s pattern, limited resources, payment scheduling, contract reward and / punishment and other factors which all affect the problem are discussed and improves the established mode. Ultimately, the outcomes of the paper are illustrated by a practical instance.

Contents Page
Acknowledgements i
Abstract ii
List of Figures and Tables v
1. Context of Research 1
1.1 Relevance of Research 1
1.2 Aims and Objectives 1
2. LITERATURE REVIEW 3
2.0 Introduction 3
2.1 Background of Project networks and Network planning 3
2.2 An Overview of Time Value of Money 5
2.2.1 Causes of Time Value of Money 6
2.2.2 The Importance of Time Value of Money 7
2.3 An overview Net Present Value Method 8
2.4 Three Sub problems of maximum net present value 9
2.5 Construction Schedule 12
2.5.1 Make a Construction Schedule 12
2.5.2 The Basic Form of the Construction Schedule 13
2.6 Method of Network Planning 14
2.6.1 The Concept of Network Diagram 14
2.6.2 Network Diagram and the Time Parameter 15
2.6.3 The key Lines, key Activities and Non-Critical Activities 16
2.7 Particle Swarm Optimization 16
2.7.1 The discrete particle swarm algorithm 16
2.7.2 Compared with other algorithms 17
2.8 An Overview of Project Network Planning Technical 19
2.8.1 The Problems of Fixed Duration and Resource Balance 20
2.8.2 The Problems of Limited Resources and the Shortest Duration 21
2.8.3 The Exchange Problem between Project Date and Project Cost 23
2.8.4 The Problem of Max-NPV 25
2.9 Deficiency of the Existing Research 25
3. METHODOLOGY 27
3.0 Introduction 27
3.1 Research Philosophy 27
3.1.1 Positivism or Interpretivism 27
3.2 Research Approach 28
3.2.1 Deductive or Inductive 28
3.3 Research Strategy 29
3.3.1 Qualitative and quantitative 30
3.3.2 Case Study 31
3.3.3 Data collection 32
3.4 Data Information 34
3.4.1 Area Choice 34
3.4.2 Project Choice 34
3.5 Research plan and data analysis 35
3.6 Problems and limitation 37
4. Findings 37
4.0 Introduction 37
4.1 project data 38
4.2 Encoding design of Variable 44
4.2.1 Decision variable 44
4.2.2 The complexity of the variables 45
4.2.3 Priority of activities’ scheduling 46
4.3 Algorithm basic step 47
4.4 The flow chart 48
4.5 Results contrast and analysis 51
4.5.1 Illustration of calculation results 51
4.5.2 Several conclusions from the results 53
4.5.3 Comparison 54
4.6 Summary of analysis 56
5. Discussions 57
6. Conclusions and Further Research 59
6.1 Conclusions 59
6.2 Further research 59
7. Reference 61

List of Figures and Tables
Figure 2.1 Gantt chart 21
Figure 2.2 Two Kinds of Network 22
Figure 2.3 Relation of Activity’s Temporal Variable 23
Figure 2.4 Relations between Date and Cost 30
Figure 4.1 Activity-on-Activity Networks 44
Figure 4.2 Activity-on-node Network in Reference 45
Figure 4.3 Main flow chart 54
Figure 4.4 Subsection Flow Chart of Activity Order’s Initialization 55
Figure 4.5 Subsection Flow Chart of Calculating Activity’s Real Start Time and Real Finish time 56

Table 2.1 The existing methods 19
Table 2.2 The difference of algorithms 26
Table 3.1 common contrasts between quantitative and qualitative research 37
Table 3.2 Content and Evaluation of the project 39
Table 3.3 Comparison of primary data and secondary data 39
Table 4.1 Activity-on-node Network's Activity Date 48
Table 4.2 Resources’ Date 48
Table 4.3 Activity’s Cost 49
Table 4.5 10 calculation results of number 5000 in PSO 57

1. Context of Research 
Pursuit of profit maximization is the ultimate aim of all economic entity. Construction unit as an independent economic entity, it also wants to pursue the maximization of profit. Net present value is often acted as a measure of incomes of a project. In recent years, Net present value maximization problem is an important part of research fields in project management. This article will cater to the trend and introduce net present value maximization emphatically.
1.1 Relevance of Research
Early in the 20th century 70's A.H.Russell began to study the Net present value maximization. After 30 years of research and development, Net present value maximization can be divided into three types of questions：
 Payment schedule in the network optimization；  
 the cash flow optimization schedule under the constraints of resources；
 Time - cost optimization in the schedule of exchange cash flow.
1.2 Aims and Objectives这里的目标和主题目还是有一些混乱，没表达太清楚，比如可以再加几条，或是修改一下。如：
1,create a decision flow model that integrates NPV/PSO with network technology
2,Apply the model to the S(这个S代表的就是后面举的中国的那个例子的名字，但具体是什么，请写出来) project
-----3，或4什么的等等，
还要有一个什么CONCLUSION——AIMS，反正写手看着处理一下，谢谢

In this paper, numerical examples, comparison and analysis, show the relationship between the project network planning techniques and the net present value method to verify the discrete variable particle swarm algorithm in solving the issue of the feasibility of maximizing the net present value of engineering practice application has some reference value. Two key objectives have been identified in this study.
 How to let payment schedule act as a decision variable and take the payment schedule of The maximum net present value and resource constraints into consideration together
 How to get net present value maximization using a improved model
 1.3 Chapter Outline
 The dissertation is divided into the following Five Chapters
 Chapter One-Seek to provide a background to the subject area and also looks to introduce three types of questions in Net present value maximization.
 Chapter Two- Through a Literature Review the researcher attempts to provide a thorough examination of current literature on the net present value, this chapter also looks to explain the deficiency of the current study and major job of this study.
 Chapter Three- The researcher considers and justifies the methods and methodologies adopted during the research process. The experiment approach adopted by the researcher is examined, together with a discussion on the research approach and strategy adopted an analysis of data analysis method. Limitations to the research are discussed together with the ethics of the research.
 Chapter Four- This section presents the findings of the research techniques applied in Chapter Three. Describe the problems studied in this paper, focusing on analyzing the problem of various factors, at last, Through an analysis of the examples, it shows how to get the maximum value of the Net Present Value of Projects.
  Chapter Five- Brings together an analysis of the findings, conclusion are drawn   which will answer the previously set out aims and objectives.

2. LITERATURE REVIEW
2.0 Introduction
In this section I will present the background for choosing the topic. An introduction to the Project networks and the Network planning, finally the research problem of the thesis and aims according to some research has been done on the problem of evaluating and maximizing the net present value of project by researchers.
2.1 Background of Project networks and Network planning 
Network planning technique is a scientific project management technology, which is component of Operational Research. Network planning technique originated from America, In the 1950s American scholars kelly and Morgan walker proposed the key route network planning, In 1958, the U.S. navy successfully applied network planning review technology that made the missile research work ahead of schedule. Then appeared the review technology, Random network planning technique, Risk stochastic network technology, Network planning technique has become the most advanced planning and management methods (Baroum ,1996).
American scholars pioneered the use of network planning, network planning technique quickly applied to project management and other fields (Wang, 2002a). Network planning optimization is a high-level network planning technology application; project management is an important element of research fields, in which the net present value maximization problem in recent years has become a hot network planning optimization (Wang, 2002b). Currently, the network planning technique has been viewed as the most effective management method in many countries, As is proved, construction period could be shorten by 20% and cost  could be reduced by 10% with the network planning technology.
The development of network planning optimization is inseparable from the application of network planning technology; meanwhile, the network optimization has promoted the application of network planning and the development of technology (Vanhoucke, 2001). Network Planning Optimization plays a very important role in the construction schedule. Firstly, Network planning is not only to determine the project's objectives, but also determines the way to achieve these objectives; it is a programmatic document to guide the construction progress. However, To get engineering with a short duration、 good quality and low cost. It is essential to optimize the network planning. Secondly, After the establishment of network plans, There are some conflicts need to be resolved at construction time, resources and other areas; If the schedule has not meet the requirement ,we should compress the continuous time of the key activities; If resources have not me the requirement, we could optimize two aspects of resources problems：fixed duration – balanced resource and limited resources - the shortest duration; if the cost has not meet the requirement, we could optimize the exchange problem between time and cost. Thirdly, actually, the optimization of network planning is a high-level technology, the network planning optimization has been an indivisible part of the network planning techniques, and it has become an important component in project management. In modern engineering, network planning optimization plays a huge role as an important mean of project management gradually (Canan, 1994).

The development of network optimization program has become an effective way to improve the project management, it is necessary to research the topic; this article (Yang, 1995) is researching the problem under this background. Profit maximization is the fundamental purpose of all economic entities, as an independent economic entities, construction units also pursue the most profit. Net present value always is measured as revenue targets of a project. The maximization of net present value considering the influence of finance has became a focus area in the field of project schedule optimization in recent years.
PATE 1
2.2 An Overview of Time Value of Money
The concept of the time value of money appeared in North financial management at the first time. This concept is a basic investment concept and a basic element in the conventional theory of finance. And it was proposed by Eugen Bohm-Bawerk, who is a vulgar economics home, in the late 19th century. In his work, The Positive Theory of Capital, he proposed capital and interest theory. The time value of money: it refers to funds in the process of production and circulation over time arising from value added. It can also be seen as the cost of the use of funds. Money does not automatically change over time in value, and only in the investment process will have benefits (John, 2007),so the value of time tends to be used risk-free rate of return on investment instead of as a rational individual will not be idle funds. It varies over time is a function of time, which took place over time the value changes, changes in the value of that part of the time value of money is the original. Combination makes sense only and labour is different from inflation. Actually, the concept of time value of money is not a new theory. Sidney Homer made the history of rate as an example in his book, to show that the value changes over time in value (John, 2007).
The time value of money generated by two prerequisites: the first one, experiencing certain period of time. And the second one, money should participate in the process of social reproduction turnover. There is several different understanding about time value of money ：First, Liquidity preference theory(Keynes, 1936): in cash profit in a timely manner and emergency stop, etc. are more convenient, lower cost, etc., the payment of interest is to give up liquidity should the remuneration. Second, the opportunity cost theory: to abandon the use of funds is equivalent to giving up revenue opportunities, and thus also equivalent to the price paid, the interest cost of such compensation. Third, The residual value of partition theory: capital to participate in social reproduction generated by the residual value should be in the funding and production operations carried out between the rational allocations of interest payments is the surplus value of this specific form of partition.
2.2.1 Causes of Time Value of Money
First, the time value of money is the embodiment of resources scarcity (Taylor, 2007). The development of economics and society needs to consume social resources. The existing social resources constitute the existing wealth, so future material and cultural products, which are created by used social resources, constitute the future wealth. As social resources is scarce and can lead to more social products，the effectiveness of the current articles is higher than the future articles’. In the money economy, money is regarded as the expression of goods value. This point means that the current money is used to pay for the current commodity and the future money is used to pay for the future commodity. Therefore，the value of current money is higher than the future value of money. Second, the time value of money is the inherent characteristic of circulating money under the Credit Monetary System. Circulating money is composed of Central Bank monetary base and deposit deriving from commercial banking system. Because of the tendency that credit money increases, devaluation and inflation become a kind of universal phenomenon，which，in turn，the value of the current money is higher than the value of the future money. Third, time value of money is the reflection of People's cognitive psychology. Because of the limitation of People's awareness，people always possess strong perception to the existing things，and more ambiguous perception to the future things. As a result，there is a general mental idea among people that pay more attention to today and neglect future. The current money can pay for the current commodity to satisfy people’ demand，however，the future money only can pay for the future commodity to satisfy uncertain demand. Because of this，the future unite value of money is lower than the current’s.
2.2.2 The Importance of Time Value of Money
The time value analysis has a lot of applications, ranging from setting up schedules for paying off debt to decisions about if to acquire new equipment (Artto, 2008). When an organization gets a capital asset, it must either borrow the funds needed for the acquisition or make use of resources currently held by the organization. In the first case, the organization will be paying interest over the life of the loan. In the latter, the organization will be foregoing the return that it could have earned from using those resources in their next best alternative use.

The theory of the time value of money always is applied to evaluate investment projects (He, 2005)，and makes decision which project can bring biggest profit. Because of some time factors，for example，investment time，production time，reaching design capacity time，annual operating costs and project life，are very different，a organization will gain different investment effects. That is unscientific to choose static analysis，so we should discount the project costs and benefits in terms of the principal of the time value of money. Do like that to eliminate the time difference，the opportunity cost and other factors, then to do competition and analysis. In a short, whether consider the dynamic relationship between money and time，it can directly affect the evaluation rationality of investment projects.
2.3 An overview Net Present Value Method
Economic evaluation of investment projects originated in American in 1930’s. After the Second World War, this method developed rapidly and was expanded to use in more and more fields (Qiang, 2008). Not only was to study the issue of building investment projects, but also used to study the production management of industrial enterprises and technical and economic policy-making, etc. At present, a systematic and scientific method has been formed. As we all know that the prerequisite to ensure that investors gain expected returns is economic evaluation of investment projects .Therefore, Selecting an objective and appropriate method of economic evaluation of investment projects is the premise of the right investment decisions. Many methods can be used to evaluate investment projects.
At present, main analysis methods are static and to be commonly used to make an investment decision (Gao, 2008). Dynamic analysis methods are based on the time value of money principles and methods. And then, they convert different periods of cash inflow and outflow into comparable amount by a comparable basis, then to evaluate and analyze the investment benefit. The net present value is one of dynamic analysis methods; it is praised highly by scholars in academia theoretically and is commonly used in practice.
2.4 Three Sub problems of maximum net present value
 Payment schedule in the network optimization
First, A.H.Russell studied the double code network diagram and established a nonlinear programming model (He, 2005), then he put forward a method to solve the model through a linearized model by Taylor expansion. Grinold did a further research; he adopted the spread of the linear model. Also, he pointed out while applied the model, the time limit for a project should be added in. Elmaghraby and Herroelen pointed that there would be some assumption in A.H.Russell’s model on the analysis of the above results. But even so, there were still may not get the optimal solution. They put forward the concept of "forest and tree” and designed a heuristic algorithm to solve the nonlinear programming.
  The cash flow optimization schedule under the constraints of resources
The cash flow optimization schedule under the constraints of resources can be subdivided into two subproblems according to the different properties (Vanhoucke, 2005): Renewable resource constraints, No-renewable resource constraints. Firstly, (Yang, 2005) puts forward a kind of integer programming algorithm; its deficiency is that the time of algorithm relies heavily on project period；in this paper Baroum assumes that only when the entire project has completed the positive cash inflows. Activities are arranged as early as possible under the logical relationship and resource constraints, when the resource conflict, it may use two kinds of detecting rules and compare them to arrange activity execution sequence; Icmeli and Erenguc put forward a branch and bound method which is the improvement of yang’, They also design the tabu search and algorithm with long-term memory; R.A.Russell designs six kinds of heuristic algorithm, Results show that  algorithms are not very good to solve all problems; Yang tests nine kinds of random heuristic rules including simulated annealing based on one thousand four hundred and forty examples, Under certain conditions, the simulated annealing method of optimization is not satisfactory. Vanhoucke thinks that project schedule is affected by logical relationship of activities and resources constraint. Based on the assumption that the consumption of resources happens at the time of completed time, they develop a branch and bound method to study two numerical examples. Secondly, Doersch and Patterson are earlier scholars to study this problem, They presented a 0-1 integer linear programming model to research funding constraints; D.Smith-Daniels and V.Smith-Daniles establish a mixed integer linear programming model to study materials constraint problem and point out the possible several schedule.
 Time - cost optimization in the schedule of exchange cash flow.
The third problem is discussed by (Liu, 2006), she is the first scholar who studies this problem and first brings the cash flow into the solving of time - cost exchange problem and established a mixed-integer nonlinear programming model；Sunder Study optimization schedule of exchanging cash flow problems under the limited resources.
Next there will be a table to illustrate the sub questions.

Sub questions Existing methods
Payment schedule in the network optimization A.H.Russell: a linearized model by Taylor expansion;
Grinold: the spread of the linear model;
Elmaghraby and Herroelen: forest and tree;

The cash flow optimization
schedule under the constraints of resources  Yang: integer programming algorithm;
Icmeli and Erenguc: branch and bound method;
Doersch and Patterson:0-1 integer linear programming model;
D.Smith-Daniels and V.Smith-Daniles: a mixed integer linear programming model

Time - cost optimization in the schedule of exchange cash flow Kelly: a mixed-integer nonlinear programming model;
Table 2.1 The existing methods
Source: author 2010
2.5 Construction Schedule
Engineering project occupies such a huge amount of resources that need a good construction schedule in the construction process (Sami, 1996). Dwight E.Smith recognizes that construction schedule is the aggregate concept of time sequence of construction and the pace of activities. It is specific planning and overall arrangement to the construction sequence、ending time and the resources required.
2.5.1 Make a Construction Schedule
In order to guarantee that the project will be finished in an orderly fashion in the construction process, making construction schedule must be paid attention. The primary task of construction is making a scientific construction schedule (He, 2005). Firstly, the schedule must have a clear goal. Usually, the time plan is the basic plan. In order to achieve this goal, it also needs other programs such as resources planning, capital support plan etc.
This paper (He, 2005) tells us the basis of making a construction schedule. Firstly, it needs the survey data on site, Projects bidding documents, project construction planning, operating plan of the construction units and construction design. This is the preparation for a schedule. Secondly, the similar plan of completed project is essential. The construction units can consult those plans and adopt the good points (Liu, 2006). The last one is the relevant laws and regulations, which should be paid attention during the period of making the schedule. The principle of making a construction schedule is also obtained from this paper. The first principle is that ensure project be completed according to the goal and make the construction unit get the profits as soon as possible. The second one is that decrease the temporary infrastructure in construction site under a reasonable scope. Avoid wasting resources and getting the max efficiency of resources is the third one and the last is that try to reduce work flow operation and organization, and damages the six-bar avoid unnecessary loss of time.
2.5.2 The Basic Form of the Construction Schedule
Construction schedule usually adopts a bar chart or network diagram (Xu, 2005). A bar chart is called gantt chart, which start to use at the beginning of the 20th century. It is simple to manufacture and has a intuitive image and easy to understand, but it is difficult to express the logical relationship activities and optimize and adjust the schedule, it also cannot calculate directly. Network diagram has used in a wide range(Cao, 2000), which is flowchart of the project activities .It can provide more information than a bar chart, for example：activity time parameters, the logical relationship, the key circuits, etc. It also can be convenient for optimize construction period and resource, so it has become a kind of commonly used method to express construction schedule.

Figure 2.1 Gantt chart
Source: L.Sunde 1995
2.6 Method of Network Planning      
Because of the popular of network planning method, it is a common method often used by people in a modern project management.
2.6.1 The Concept of Network Diagram
Network diagram is a kind of orderly map which is composed of arrow lines and node (Chen, 2006). It can be divided into double code network diagram and single code network diagram according to different meanings represented by the network diagram arrow lines and nodes. In a double code network diagram, the arrow lines represent activities, nodes represent events. An event is a state, which represent a logical relationship. In a code network diagram, the arrow lines represent the logical relationship between activities, nodes represent activities. Figure 2.2 shows the two different meanings of network diagram, Figure represents two events named i、j, an activity named A; Diagram b represents two activities A and B. It can be seen from figure 2.1 that single code network diagram has strong ability of logic expressions, the expression form is so in accord with people’ thinking that it is easy to accept. In fact the double code network diagram is a special case of code network diagram in the calculation of the parameters.

Figure 2.2 Two Kinds of Network
Source: Tavares L V 2002
2.6.2 Network Diagram and the Time Parameter
Activity is the smallest unit after the decomposition. There are Virtual activities in the network diagram. Virtual activities don't consume time、resource and expenses, which only show a relationship. The activity in front of one of network activities is called the former activity, behind one is called the latter and the activity at the same time calls concurrent activities. Activities start from the network plan which is before the one activity is called the first activity, and others are called follow-up activities.
The main time parameters of activities in network diagram are that Duration Di, Early Start Time ESi, late Start Time LSi, early finish time EFi, late finish time LFi, Real start time ASi, Actual Finish Time AFi, Free Float FFi, Total Float TFi. This paper also shows each physic meaning of time parameters.

Figure 2.3 Relation of Activity’s Temporal Variable
Source: Chen 2001
2.6.3 The key Lines, key Activities and Non-Critical Activities
The line consisted of activities whose total time is zero is called the key line. The duration of activities in key lines and the overlapped time decide the total duration. Due to the total time is zero, the activity duration, start and end time will affect the total duration. So these activities are called key activities (Xu, 2005). The key line is important for project schedule and it is often the key of project schedule control. Sometimes, there is more than one key line. Non-critical activities exist float time, it means that start time is not fixed. Does not affect the total time, the duration of these activities can be adjusted in a certain range and the start time can be appropriately delayed. Non-critical activities often become the key to optimize network planning. Optimization of resources、cost and construction period is realized by rationally using float time of the non-critical activities.  
2.7 Particle Swarm Optimization
Particle Swarm Optimization (PSO) suggested together by American social psychologists James-Kennedy and electrical engineer Russell – Eberhart in 1995. The basic idea was inspired by the results of birds’ group activities and uses the model of biological community of the biologist Frank. Since this algorithm was put forward, many scholars paid close attention. At present, this algorithm has become an important branch of optimization algorithm and applies to many areas successfully (Zeng, 2004).
2.7.1 The discrete particle swarm algorithm
From the analysis of the preceding chapter, there are three main variables in this algorithm: mode variable, pay variable and activity’s sequence variables (Zeng, 2004). The three variables are discrete which mode variable and pay variable is 0-1 variables, activity’s sequence variable is integral space variable. The characteristics of these variables determine that it is necessary to apply the discrete particle swarm algorithm to solve the maximum net present value in this dissertation.
2.7.2 Compared with other algorithms
 Genetic algorithm
Genetic algorithm was proposed in the 1960s. American scholar John H. Holland studied biological genetic method at the earliest (Tang, 2000). In 1967, his student named J.D.Bagley put forward the concept of genetic algorithm. Genetic algorithm needs to encode problems (generally adopts binary form). The algorithm starts at randomly initial population, produces next generation through some operator (selection, crossover and mutation), then sets the new generation of the species at start and repeats this process until termination conditions is satisfied(Tang, 2000). At present genetic algorithm has formed a set of mature theoretical system and has applied extensively in many problems. Particle swarm algorithm has much in common with genetic algorithm. For example: both of them are random search algorithm and have global search capability; update according to the individual's adaptation value. Compared with genetic algorithm, the particle swarm optimization algorithm has the following advantages: it has good memory which can remember the best solution; coding technology is relatively simple and practical; Algorithm convergence is unidirectional and search speed is fast (Zhang, 2005).

 Ant Algorithm
Ant algorithm was born in the early 1990s which raised by Italy scholars Colorni and Dorigod(Zhang, 2004). This algorithm takes example by the ants foraging behavior characteristics whose principle is enhanced positive feedback learning system. There are two important characteristics of the algorithm: positive feedback mechanism and distributed parallel searching ability. Using this feature, the algorithm can quickly find the optimal solution of the problem. The algorithm has been used in salesman problem, the second assignment problem, vehicle scheduling and it shows a fairly good performance. Particle swarm algorithm also has in common with ant algorithm. For example: Randomness, global characteristic. Ant algorithm has its own advantages. Such as: Enhanced and distributed search which improve the performance of the algorithm. But the ant algorithm has some faults(Zhang, 2004). For example: stagnant and search speed is slow. Besides ant algorithm’s memory is inferior to particle group algorithm. Next the table 4.4 will show the difference of those algorithms.

The algorithm  Advantage  disadvantage
Particle group algorithm  Good memory
 Simple coding technology
 Search speed is fast
 practical Centralized search
Genetic algorithm  Global search
 Mature system info  Complex coding technology
 Algorithm convergence is bidirectional
Ant algorithm Enhanced and distributed search  stagnant
 search speed is slow
Table 2.2 The difference of algorithms
Source: Author 2010
PATE 2
2.8 An Overview of Project Network Planning Technical
Usually, A good network schedule should have the following features (C.S.Sung, 1995): low input of resources, balanced use of resources, low cost, short construction period, good quality, As a result, It is necessary to optimize the first network plan .The optimization of network planning determines whether the progress of the project plan is the best one. Under the conditions (established period, cost, quality, resource, etc), according to a target, It can be adjusted the start time of the activities continuously to seek a satisfying program, which is called the optimization of network plan  according to different optimization goals. The optimization of network plan can be divided into time, cost and resources. It includes the problems of fixed duration and resource balance, the problems of limited resources and the shortest duration, the problem of exchanging construction period and cost, the problems of maximizing the net present value.
2.8.1 The Problems of Fixed Duration and Resource Balance
The goal of such optimization is that the utilization of resources should be balanced as much as possible during the construction, meanwhile, avoiding frequent and severe phenomenon including peaks and valleys (Chen, 2006).The principle of the optimization is that using the time difference between the activities to adjust the time parameter of non-critical activities and adjust the order of resource using, making sure the dynamic curve of resource allocation as smooth as possible. Measuring the extent of the imbalance of resources is usually expressed as variance                                 (1)
Where  denotes the amount of resources needed at time t;
Denotes the average resource requirements;
  Denotes the total time of construction.
Because  and  are constant, to minimize  2, we can minimize
,                                           (2)
where  denotes the amount of resources needed in time i.
The main research methods are analytical method and the analytical method is to find the optimal solution in theory, it includes point decomposition and strategy space method, the heuristic method is a "peak load shifting method", namely using the peak and valley of resources and adopting a “balance " strategy(Xu, 2005). The classical methods are Jishi Bo’s balanced process and Wister’s balanced process (Xu, 2005). In recent years, many scholars have adopted heuristic genetic algorithm, ant algorithm, artificial neural network algorithm and PSO (Particle Swarm Optimization) to study the issue.
2.8.2 The Problems of Limited Resources and the Shortest Duration
In the implementation of any project, we must consume a variety of resources but the resources are limited(Chen, 2006), as a result, the activities in network planning are not only constrained by the logical relations but also constrained by the maximum supply of the resources. The important thing to solve such problems is how to effectively adjust the various activities’ executive order when these activities resource conflict, after that, minimize the total duration of the delay.
Suppose a project requires Z kinds of different resources, the supply at time t is ，where is a constant, In the continuous time, the resources needed of activity I are  ,where   is a constant. So, in the whole network plan, the total demand of resource z is expressed as                                      (3)
And the lower bound of the shortest duration is
                                                          (4) 
If we do not take resource constraints into account, the length of critical path in network plan calculated is , if we take resource constraints into account, the schedule must satisfy the following formula:
.                                           (5)
The key to solve the problems of limited resources and the shortest duration is how to arrange the execution order of activities (Shou, 2004). Many scholars have divided it into exact algorithm and heuristic algorithms, heuristic includes the algorithms that based on activities priority rule and other intelligent optimization methods appeared in recent years. Among these methods, the algorithms that based on activities limited rule are popular. These heuristic algorithms mainly research the Schedule Generation Scheme (SGS).SGS is a method that generate a complete and feasible project schedule by gradually extend partial schedule. Because of different methods of expansion, SGS can be divided into serial SGS and parallel SGS. Serial SGS includes N (N is the number of events) stage, every stage selects a specific activity from the practical activities that focus on the priority rules, and arranges the activities as soon as possible which should meet the constraints of logic and resources. Practical activities includes in the current phase of the collection of all time and not scheduled to begin before all activities have been lined up tight schedule of activities.
2.8.3 The Exchange Problem between Project Date and Project Cost
The total cost of Project is making up by direct costs and indirect costs (Wang, 2001). Generally speaking, direct costs such as construction cost and the use amount of resources Increasing when Project date cut down, indirect costs such as management and safety will reduce when Project date cut down. The Exchange Problem between Project date and Project cost is to find the lowest point of cost and the Schedule of net plan in the context of Project period meet the requirements. Fig.2.3 shows the Relation between Date and Cost. Point A means the Project date when the cost is the lowest.                           

Figure 2.4 Relations between Date and Cost
Source: Shou 2004
The substance of the Exchange Problem between Project date and Project cost is to choose the best combination between date and cost to make the rush rate lowest in the net plan (Shou, 2004). The theory contains two assumptions: all the direct costs of the work in net plan have Non-increasing linear relationship, the cost rate is P; the relation between indirect costs and Project date is Single increasing linear relationship, q is the indirect costs rate. We often uses optimization such as Progressive method, Reductionism, Labelling, Linear Programming. We always use Progressive method in the schedule management of project, It is used in the base that Various activities adopt normal time and cost plan, then use the duration of key activities and cost relationship as basis. We must constantly adjust network plan after considering the Possibility of Shortening the critical activity duration and the constraint relations of time difference between non-critical activities to get a Series of project schedule.
2.8.4 The Problem of Max-NPV
The Problem of Max-NPV Considers the network optimization program from the financial side ( P.Pinder, 1996). The problem regards maximizing the net present value as optimization objective for the project's progress; it emphasizes not resource balance and the shortest project date but revenue maximization and shorter project date and higher resource utilization. The early studies of Max-NPV use approximate linear programming to solve the problem, Later there will be some analysis of Algorithms such as branch bound method and many heuristic algorithms. Heuristic algorithms have been the most important method to solve the problem at present.
PATE 3
2.9 Deficiency of the Existing Research
In this paper (Zhang, 2005), it tells us deficiency of the existing research. It can be summed up in three sub problem. The first one is deficiency of the objective function. As objective function directly reflect optimized objectives, which is reasonable or not will directly affect the reality of the research. The existing target basically has the following three deficiencies：Firstly, it is not in accord with the enterprises which seek for profit maximization；Secondly, it does not consider the time value of money and the dynamic optimization of question in the whole project cycle；Thirdly, it does not consider the owner's payment and the rewards and punishment. In practice, the construction enterprises think about data-cost which is closely related the owner's payment.

The second one is no consideration of resource constraints or only a single resource constraint (Zhang, 2005). In practice, the consumption of resources occupied most of construction investment. Any project construction needs many resources. Decreasing the construction period is realized by increasing resource allocation, so resource constraints are inevitable. All activities start to use a certain resource simultaneously that will cause a bottleneck. Increasing resources or extending the working time of the resources will decrease the construction period. So the resource is an essential factor in a network plan optimization.
The third one is the simplification execution mode (Zhang, 2005). In practical engineering, construction units according to the progress of the construction decide how much of the facility resources、the additional cost and the length of construction period. Then determines the extended or shorten the construction activities, which mean that activities have a variety of execution modes. Construction unit choose a reasonable mode to perform the activities according to the practice situation. Single mode makes the research results different form actual ones.

3. METHODOLOGY这块儿的研究方法也没太方清楚，developing decision flow model，就是要把用的技术方法什么的，都加入进来，在这里说一说
Link to literature review a gap/deficiency ,还有怎么样建立这个模型，用什么方法推导出来的，等等
3.0 Introduction
Within this Chapter the author will justify and identify how he plans to carry on the research with a consideration for the interrelated method. In choosing specific research methods it is significant to justify the theoretical philosophy and perspective that our choice of research is based on. Crotty (1998) showed that a researcher needs to identify the methods and methodologies employed which “reaches into the assumptions about the reality” we adopt into our research.
3.1 Research Philosophy
The philosophy used in this paper by the author provides a framework on how the entire research process is planned and carried out (Trebilcock, 2006). In determining the research philosophy used we must illustrate what is knowledge and how it is got firstly, these questions are related to the Epistemological viewpoint of the researcher, Epistemological is identified as being concerned with if the natural sciences or social sciences can give us with the necessary knowledge in our chosen theme (Bryman and Bell ,2003).
3.1.1 Positivism or Interpretivism
The primary Epistemological philosophies identified by (Collis and Hussey ,2003; Bryman and Bell, 2003) are that of the Positivist and the Interpretivism (or Phenomenology) way. The Positivism perspective is argued as being involved in the application of the ways of the natural sciences; it represents a more scientific methods and focuses on the capable for defining research through more systematic and statistical approach, leading to highly structured methodologies that generate data which can be effortlessly replicated in subsequent research (Bryman and Bell, 2003).
Based on the concept which the world is comprised of upon a lot of truths, interpretivism is an Epistemological position (Trebilcock, 2006). There must be more than one answer to the research question. That is why it is essential to decide the significances and intentions behind individual actions for the purpose of understanding them. Interpretive is argued that strongly associated with qualitative approaches to research because of it focusing on the meaning, while it is compared with the measurement of social phenomena (Collis and Hussey, 2003).
Based on the research purpose stated in the Introduction, although it is obvious that these cannot be replied from a systemic or scientific approach which is featured of the interpretive standpoint, it can only be replied from a Positivist perspective that seeks to comprehend the true of a situation by acquiring a rich insight into the theme area (Trebilcock, 2006). 
3.2 Research Approach
In choosing the research approach it is significant to decide the nature of the relation between research and theory, the research approach is dependent on whether the theory is formed as a prolusion to the research process, or an inference of the research process by Saunders et al. (2007).
3.2.1 Deductive or Inductive
The deductive way to research design is based on logical reasoning(Trebilcock,2006). It assumes an explicit knowledge and comprehension of the theoretical background prior to the data being gathered. Ghauri and Gronhaug (2005), permit the researcher to get conclusions from a premise that is known to be genuine.  It is in contrast to the inductive approach in which data is gathered and theory is then formed as conclude of the research.
Within this research a overview of the in being theory and literature identified a list of pre decided subjects which composed the responsive SC, which the research approach was subsequently structured around; It is representative of a more deductive approach to the research process (Saunders et al. 2003). The researcher thinks that insert the data collection process with an explicit theoretical knowledge which will add dependability to the result. But the researcher was also penetrating not to let pre-decided frameworks prohibit the growth of new insights which is representative of a more Inductive approach to research design. As a result, the researcher was based on a predominantly deductive method, but was also probable to be effected by the inductive perspective (Trebilcock, 2006).
Meanwhile some authors accept the deductive approach as being identified with the philosophy of Positivism. The characteristic of inductive and deductive approaches into detailed exemplifications is misleading and serves no actual value (Saunders et al. 2003).
3.3 Research Strategy
There are a lot of researches strategies which can be adopted, meanwhile some of these strategies pertain to the Positivist and Interpretivism philosophies .Allocating strategies to especial philosophies is excessively simplistic that is argued by Saunders et al. (2003). The following identifies plentiful strategies which can be employed that are part of both Positivist and Interpretivism philosophies:
 Experiment
 Survey
 Case Study
 Action Research
 Exploratory, Descriptive and Explanatory studies
In choosing a research strategy it is crucial to select a right strategy that would answer the stated research objectives. The researcher chooses to do a case study analysis.
3.3.1 Qualitative and quantitative
Qualitative and quantitative research strategies are two kinds of methods adopted in research. "Qualitative research is a research strategy that usually emphasizes words rather than quantification in the collection and analysis of data". (Bryman and Bell, 2003). In this dissertation, quantitative approach will be adopted. Whilst there will be a small part of qualitative analysis used to response some conditions in the case precisely.
“In very broad terms, it was described as entailing the collection of numerical data and as exhibiting a view of the relationship between theory and research as deductive, a predilection for a natural science approach (and of positivism in particular), and as having an objectivist conception of social reality" (Bryman and Bell, 2003).  Therefore, in this dissertation a quantitative approach will be adopted.

There are the contrasts between quantitative and qualitative approaches in table 3.1.
Qualitative  Quantitative
Words Numbers
Points of view of participants Point of view of researcher
Research close Research distant
Theory emergent Theory testing
Process Static
Unstructured Structured
Contextual understanding Generalization
Rich, deep data Hard, reliable data
Micro Macro
Meaning Behavior
Natural settings Artificial settings
Table 3.1 common contrasts between quantitative and qualitative research
Source: Bryman and Bell 2003
3.3.2 Case Study
Case study is defined as the ‘development of detailed, intensive knowledge about a single “case”, or a small number of related “cases”’ by Robson (1993:40) (Cited Saunders et al., 2000). Morris and Wood (1991) indicated that case study can help to acquire a rich understanding of the context of the research (Haiyu MA, 2009). Besides, with case study, it is easy to analyze comprehensively the complex relationships and various conditions of logistics. In this dissertation, the information of a Chinese sub-project named Hubei Beijing-Zhuhai expressway Da Wu Bei Duan (JZDWBD-V) will be presented and used ant colony algorithm to solve. Beijing-Zhuhai expressway is one of the main national roads, which run through from north to south in China. Its hubei segment passes through DaWu. It affects the north-south railway transport in China. The project started on February 1, 2002,and finished on June 20 ,2002.The results calculated in this dissertation will compare with other heuristic algorithm (Chai, 2005).
3.3.3 Data collection
The data, which has already been collected by some other people and is re-analyzed for a new purpose, is secondary data (Saunders et al., 2000). Because the project—JZDWBD-V is used as a case in this dissertation is a very representative of actual project and it has been completed, so enough information about this project can be collected. The data of the project can be got from public plan of the project, reports of JZDWBD-V itself, People's Daily, magazines, newspapers of Chinese government, and so on. Moreover, compared with primary data, secondary data is easier to get with modern media. The process of collecting data will be more time-saving and the data which can be collected should be relatively completed. So in this dissertation, the method of case study will be used to apply the model and achieve the aim. There also will be a table illustrate the difference between primary data and secondary data.

Source Content Evaluate
People’s daily Beijing-Zhuhai expressway is one of the main national roads, which run through from north to south in China. Finished on time
Magazine The project started on February 1, 2002, and finished on June 20, 2002. Achieving convenient traffic
Newspaper of Chinese government The total project contract value of JZDWBD-V is 160.077 million Yuan Qualified acceptance
Table 3.2 Content and Evaluation of the project
Source: Author 2010
the type of survey advantages disadvantages
primary data  Position-relevant  take too long
 high costs
 high requirements to investigators
secondary data  Simple and fast
 Timesaver, low costs  May be some difference from the purpose of investigation
 The authenticity and reliability of data need to be reviewed and appraised
 The source of the data
Table 3.3 Comparison of primary data and secondary data
Source: Author 2010
3.4 Data Information
3.4.1 Area Choice
In this dissertation, the project named JZDWBD-V in China is chosen as a case to study, one reason of which is that China is still an area where Net Present Value problem has not developed in to a high level and developed lately while it is experiencing a high speed growing period.
With China becoming the centre of production and purchase all over the world, now China gets an uncommon chance for engineering project because of economic globalization and special conditions of China(Fueling, 2008). In the period of the rapid economic development, there are some super Chinese project planning projects emerging, for example: JZDWBD-V , although Chinese industry has not reached a mature stage and still has the problem and most of current Chinese network project cannot satisfy the demand of the market because of still be in its primary stage.
In this situation, the problems emerging and benefits network project providing to deserve special mention. So China is chosen to study further.
3.4.2 Project Choice
This dissertation will be based on a Chinese project called JZDWBD-V. JZDWBD-V is a sub-project of JZDWBD which is the fifth contract period. The study of this project is believed to provide a further understanding of external environment of Chinese project and operations and strategies inside of the project. The total project contract value of JZDWBD-V is 160.077 million Yuan, 5 percent has paid first in the first contract period, and another 5 percent which works as quality warranty is paid if there is no big quality accident happened during the warranty. So the following funds are 90 percent of the JZDWBD-V.
3.5 Research plan and data analysis
In order to get enough and believable information for this research, public plan of the project, reports of JZDWBD-V itself, People's Daily, magazines and so on will be searched, compared, classified and adopted. So the amount of information and reliability can be guaranteed (He, 2006).
Mainly two aspects of JZDWBD-V project will be focused on:
 Make the project construction date is the shortest
 Make the project income maximization
First and foremost, the background of JZDWBD-V will be introduced. This first step will provide a general understanding of the project, so we can get a general impression of JZDWBD-V. Then, the most important information about JZDWBD-V’s network planning it involved will be given:
 Resource constraints
Construction projects need all kinds of resources in the work progress (Zhang, 2005). According to the different nature of resources, they are divided into: renewable resources, nonrenewable resources and double resource constraints. Renewable resources usually refer to available quantity under restrictions in each period. Common renewable resources are human, equipment, etc. Nonrenewable resources usually refer to available quantity under restrictions in the whole period, for example: raw material, etc. Double resource constraints usually refer to available quantity under restrictions in each period and the whole period, for example: funds, etc.
 The practical start time and completion time
The practical start time of activities of network planning under resource constraints often becomes the key of optimization (Shou, 2004). This problem is called schedule mechanisms. Determining the real start time is the equivalent of determining scheduled plan.
 Cash flow analysis
How to evaluate a project’ interest? It needs to be measured according to the specific evaluation index. It can be divided into static and dynamic evaluation indexes according to consider the time value of money or not. Dynamic evaluation indexes of more intuitive to reflect the profitability of the project. Dynamic evaluation indexes usually include dynamic investment recoupment period, the dynamic investment effect coefficient, net present value and internal rate of return, etc. Among them, net present value is a dynamic evaluation index which is used frequently (Huang,  2002).
 Project rewards and punishment
In practice, days for construction in the contract are general longer than in the network planning (Chen, 2006). So the choice of awards contract increased the possibility of income for construction builder. Using awards contract has the following advantages: 1) Relative to total price contract, there is much less risk of construction builder; 2) Construction builder will choose reasonable activity mode, which can not only shorten the construction period, but obtain the reward to increase profits. 3) Due to the existence of rewards, it makes the construction builder’s income have security. Rewards can be gained in the situation which the project can be finished ahead of the schedule by the construction builder and project acceptance.
3.6 Problems and limitation
Due to just one project are concentrated on, the value of this dissertation may be limited because it is not able to reflect all relevant areas of Chinese projects. However, the case chosen in this dissertation is very typical, so most of relevant issues will be tried to be covered. The data in this dissertation are secondary data, which cannot be real-time and creditability may be a problem. However, in data collection process, the last data will be pursued. And because all data comes from regular media, so the accuracy and creditability should be appropriate. Just with qualitative and some issues may not be able to be presented very exactly and clearly, so small part of quantitative data will be used. Furthermore, it is possible that the research contains some bias because when using the research method of qualitative, some personal opinions may be combined.
4. Findings
4.0 Introduction
In this chapter, Ant colony algorithm is applied in JZDWBD-V to solve the maximum net present value and will be compared with other algorithm to show its benefits. Within the analysis, the theory covered in Chapter 2—Literature Review will be used to help analyze and tell the difference between conditions in China and general issues raised by authors. The questions about specific objectives of this research raised in methodology will be answered. And at the end of this chapter, a summary will be given.
4.1 project data  
Figure 4.1 is the project network diagram, and each activity is defined two exec mode---normal mode and crashed mode. Table 4.1 shows all activities’ currency quantities and data and cost in different exec mode. Other parameters of the project are as follow: the payment time (K)is 4; According to the previous operation data, the owners’ expected earnings(B) estimates for 2899 Yuan; The discount rate(ɑ=0.0002) sets as the construction bank loan interest rate; The project will set the start time as 0; the deadline (D) is 22; the proportion (λ) of cost sharing of project finance is 0.01; Because of this project cost (especially materials cost ) happen in start time ,so the ξ is 0.8.
 

ActivityID Name
1 Repair roadbed
2 Compart drainage ditch and rimstone
3 Emulsify bitumen up-slurry seal
4 Emulsify bitumen down-slurry seal
5 Cement concrete pavement
6 Cover cement
7 Pave galvanized tube
8 Hardened verge
9 Set toll booth and telephony platform
10 Tail-in work
Figure 4.1 Activity-on-Activity Networks
Source: He, 2006
It can be seen that this example uses double codes network diagram. Because this paper use single code network diagram as the research object, so it will be transformed into single code network diagram and shown in figure 4.2. 

ActivityID Name
1 Repair roadbed
2 Compart drainage ditch and rimstone
3 Emulsify bitumen up-slurry seal
4 Emulsify bitumen down-slurry seal
5 Cement concrete pavement
6 Cover cement
7 Pave galvanized tube
8 Hardened verge
9 Set toll booth and telephony platform
10 Tail-in work
Figure 4.2 Activity-on-node Network in Reference
Source: He, 2006.
In the figure, node S represents begins activities, node F represents end activities, node E1 and E2 represent virtual activities separately. These four activities are not time consuming and resources consuming.
Activities Numbers mode resources date Cumulative value
  Resource1 Resource2 Resource3 
1 normal mode 12 0 0 5 700
Crash mode 24 0 0 3
2 normal mode 16 0 2 6 2000
Crash mode 16 4 0 5
3 normal mode 8 0 0 3 300
Crash mode 14 0 0 2
4 normal mode 6 2 0 4 600
Crash mode 6 0 2 3
5 normal mode 6 0 0 3 200
Crash mode 10 0 0 2
6 normal mode 12 4 0 4 1600
Crash mode 14 0 3 6
7 normal mode 8 0 0 5 600
Crash mode 2 2 0 6
8 normal mode 6 0 0 6 400
Crash mode 4 0 1 4
9 normal mode 12 3 0 8 2000
Crash mode 12 0 3 6
10 normal mode 14 0 0 4 600
Crash mode 4 4 0 3
Table 4.1 Activity-on-node Network's Activity Date
Source: He, 2006
Table 4.2 lists the main parameters of resources in the example.
Resource’ type Maximum amount Resource costs
Resource 1 28 10
Resource 2 5 40
Resource 3 3 70
Table 4.2 Resources’ Date
Source: He, 2006.

It can be got the cost at normal mode and crash mode separately from the table 4.1 and 4.2. The specific data shows in table 4.3.
Activities Numbers Mode Cost
1 normal mode 600
crash mode 720
2 normal mode 1800
crash mode 1600
3 normal mode 240
crash mode 280
4 normal mode 560
crash mode 600
5 normal mode 180
crash mode 200
6 normal mode 1400
crash mode 1400
7 normal mode 480
crash mode 500
8 normal mode 360
crash mode 440
9 normal mode 1920
crash mode 1980
10 normal mode 560
crash mode 600
Table 4.3 Activity’s Cost
Source: He, 2006.
4.2 Encoding design of Variable
Encoding design is the connection of algorithm and problem which is a process that translates variables abstracted in the problem. Encoding design should combine the characteristics of problem and the characteristics of algorithm.
4.2.1 Decision variable
The objective in this dissertation is that study the net present value maximization problem in network project. Activities’ executive sequence and start time is connected to each factor. Cash inflows and outflows are closely related to activities’ real start time, which are the major factors to affect the optimizing targets. Resource is one of the important factors to affect activities’ real start time. Under the condition of resource constraints, activities’ real start time is no longer simply decided by the logical relationship of activities, but determined by the resource constraints and logical relationship of activities jointly. Executive mode is one of the important factors in optimal result and is also a factor that should be considered in the evaluation function. Because executive mode is related to activities, executive mode variable is one to one correspondence with activity’s sequence. Besides payment is a necessary factor to consider which affects the optimal results, but it is not the key factor to the final project progress plan. This factor is the main influence factors of the net present value. it is also associated with activity and the activity’s sequence. Therefore, it will be linked with activity’s sequence.
The main variables in the algorithm are as follows:
Payk: The amount of payment in the k times;
Pn: whether the activity n is paid or not;
Lnm: executive mode of activity n;
RSn, RFn: The real start time and the real finish time of activity n;
RD: another name of RFn;
4.2.2 The complexity of the variables
Among three main variables, the first one is integral space variable. Those combinations are related to the number of activities theoretically. There are   kinds of combinations. But since the beginning and end of the project must be arranged at the first and the last activity in network chart, the combination number are . Besides, there are constraints of logical relationship among activities, the number are necessarily less than .The second one is 0-1 variable. Those combinations are related to the number of activities theoretically, there are 2N kinds of combinations. The practical combination is corresponded to theoretical one. The third one is also 0-1 variable. But its theoretical combination is not only affected by the number of activities, but also by the number of executive mode. The combination numbers are MN. The practical combination is corresponded to theoretical one. This clearly proves the complexity of variables is less than  *2N*MN, more than 2N*MN. It belongs to combinatorial optimization problem. The more complexity of the variable is, the higher requirements of optimal performance are needed.
4.2.3 Priority of activities’ scheduling
In this dissertation, the production of activities’ sequence adopts the serial mechanism. During the production, it is necessary to choose a activity which satisfy the condition of resource constraints, logical relationship constraints. But it is random to choose a activity among the assemble which satisfy the conditions. This involves Priority of activities’ scheduling. Many scholars have put forward many solutions respectively.
Luo(2004) puts forward a kind of heuristic algorithm of priority of activities’ scheduling. This algorithm emphasizes randomness. Its main principle is that due to the constraints of activities’ logic relation; it will generate a lot of infeasible solution by randomly generated. The algorithm considers a activity which still has not arranged by a fixed order, and the whole selection process is generated from left to right successively. At each stage, there is a set of practical activities’ scheduling, and it gives a priority of conflicting work randomly. This process has been repeated until all work has finished the selected arrangement. The essence of this method is that in the set of practical activities, chooses the activity randomly, which is without priority with the equiprobable model.
The efficiency of random sampling depends mainly on random functions. Shou(2004) Mentions a solution to solve various activities’ priority, which is called based on the value as regret random sampling methods. The method combines a prioritized rule commonly used in the heuristic algorithm. The prioritized rule is that examines an activity in a feasible set named Q, and make the selected probability is related with its priority, meanwhile ensure the sum of probability of all activities in the feasible set is 1. The random function is as follows:
                                              (6)
is the probability of activity (i, j) selected;
  is the largest D-value between the priority of activity(I, j ) and other activities in set Q;
  is parameter, Generally, it is greater than zero and the value is often set as 1. This ensures the lowest priority activity also has certain probability to be selected;
  is used to control the stochastic process.
According to the above definition of probability, it can choose an activity randomly in the practical set Q. The probability of activities selected is reciprocal to the priority. The smaller the priority, the probability of activities selected is larger. It can be anticipated that the prioritized rule will have effect on the project schedule by generated randomly. Therefore, the prioritized rule which is based on the random sampling is used frequently at present.
This dissertation will adopt the random number based on the system time to determine the activities priority. Firstly, the random number based on the system time is produced by a random function used in the VB language, which is used as the priority of activities scheduling. When there are a lot of choices in the feasible set, the activities’ scheduling will be determined by the size of the random number.
4.3 Algorithm basic step
 Initialize particles’ random position and speed according to the established initialization
 Calculate each particle’s adaptive value
 For each particle, let the adaptive value compare with the best position’ value which has experienced, if it is better, it will be set as the current best position.
 For each particle, let the adaptive value compare with the best position’ value which has experienced in the whole situation, if it is better, it will be set as the current global best position.
 Make the particles’ speed and location iterated according to formula
 If terminal conditions are satisfied, the algorithm ends. Otherwise, return steps 2
4.4 The flow chart
Based on the previous chapter, this paper uses the discrete particle swarm optimization algorithm to solve the maximum net present value. The main flow chart is shown in figure 4.3.

Figure 4.3 Main flow chart
Source: Author 2010
Each subfunction of main flow chart needs more detailed steps to be realized. Next we will give illustration of some subfunction using flow chart. Figure 4.4 reflects initialization position of main flow chart and the initialization procedures of activity sequence variable-speed. Figure 4.5 reflects the real start time (RS) and real finish time (RF) of main flow chart.

Figure 4.4 Subsection Flow Chart of Activity Order’s Initialization
Source: Author 2010

Figure 4.5 Subsection Flow Chart of Calculating Activity’s Real Start Time and Real Finish time
Source: Author 2010
4.5 Results contrast and analysis
4.5.1 Illustration of calculation results
The results from last iteration are set as the approximately optimal solution Because of the randomness of the algorithm; the calculation shall be carried out many times and got the statistic results. Table 4.5 shows the 10 calculation results of number 5000 in PSO.
下面这一整个图表，不知道怎么回事，老师说他一开始看的时候，觉得奇怪看不懂，框框里面那一串串的数字是从哪里来的，怎么看不懂，代表什么呢，可以把这个图表换个更简单明了的图吗？？

Serial number activities’ actual start time activities’ real finish time activities’ mode activities’ paid NPV
1 0 0 5 5 8 8 8 12 12 18 5 5 8 8 11 12 14 18 18 21  1 2 1 2 1 2 1 1 2 2  0 1 0 0 0 1 1 0 0 1 1029.097
2 0 0 5 5 8 8 12 12 12 18 5 5 8 8 11 12 18 18 18 21 1 2 1 2 1 2 1 1 2 2 1 1 0 0 0 0 1 0 0 1 1029.784
3 0 0 5 5 8 8 12 12 12 18 5 5 8 8 11 12 18 18 18 21 1 2 1 2 1 2 1 1 2 2 0 0 1 1 0 1 0 0 0 1 1027.312
4 0 0 5 5 8 8 12 12 12 18 5 5 8 8 11 12 18 18 18 21 1 2 1 2 1 2 1 1 2 2 1 0 1 0 0 1 0 0 0 1 1027.221
5 0 0 5 5 8 8 8 12 12 18 5 5 8 8 11 12 14 18 18 21 1 2 1 2 1 2 1 1 2 2 0 0 0 1 0 1 0 0 0 1 1026.784
6 0 0 5 5 8 8 8 12 12 18 5 5 8 8 11 12 14 18 18 21 1 2 1 2 1 2 1 1 2 2 0 0 0 1 0 1 0 0 0 1 1026.784
7 0 0 5 5 8 8 12 12 12 18 5 5 8 8 11 12 18 18 18 21 1 2 1 2 1 2 1 1 2 2 0 1 0 0 0 1 1 0 0 1 1029.480
8 0 0 5 5 8 8 12 12 12 18 5 5 8 8 11 12 18 18 18 21 1 2 1 2 1 2 1 1 2 2 1 1 0 0 0 0 1 0 0 1 1029.784
9 0 0 5 5 8 8 12 12 12 18 5 5 8 8 11 12 18 18 18 21 1 2 1 2 1 2 1 1 2 2 1 0 0 0 0 1 1 0 0 1 1026.677
10 0 0 5 5 8 8 8 12 12 18 5 5 8 8 11 12 14 18 18 21 1 2 1 2 1 2 1 1 2 2 0 1 0 0 0 1 1 0 0 1 1029.097
Table 4.5 10 calculation results of number 5000 in PSO
Source: Author 2010
4.5.2 Several conclusions from the results
 Because of the large scale problems and the complexity of the variables, the optimizing performance is not stable, especially in the optimal payment schedule.
 Each iterative result is not identical. There are two reasons. Firstly, it is related to the randomness of the algorithm. Every time the random Numbers are produced in different iteration. Secondly, the results effected by seeking for the optimal performance and complexity of the problem. It is difficult to get the optimal solution from combinatorial optimization problem, and it mostly only gets approximate solutions. From this point of view, this paper has got some of the approximate solution of the combinatorial optimization problem which is accord with the characteristics.
 The approximate solutions of multiple optimal solutions are obtained. The NPV of the project, payment schedule and each activity’ actual start time of each scheme is different, but the total time of construction and each activity’ mode is the same. It can be seen from the calculated results that there are two major schemes. Each activity’s start time of the first scheme is{0 0 5 5 8 8 12 12 12 18} and the other is {0 0 5 5 8 8 8 12 12 18}.
 Except the virtual activities, the optimal time of each activity is {0 0 5 5 8 8 12 12 12 18}, the optimal mode of each activity is {1 2 1 2 1 2 1 1 2 2 }, the optimal payment schedule of each activity is {1 1 0 0 0 0 1 0 0 1}, The optimal time of construction is 21, the maximum net present value for the project is 1029.784. It can be seen that payment schedule has certain effect on the final result.
4.5.3 Comparison
对比这部分，也要一个表格，最好是一个TABLE对比一下，老的方法和新方法的区别，和PSO的区别什么的？这样更明确看出来，容易懂
There are some different points with two optimization model [25] which combines contractor’s and the client’s viewpoints respectively. For example: The model of He (2006) fixes the payment on 4 landmarks (2,4,5,7); otherwise payment scheme works as a decision-making variables in this paper . The model of He (2006) considers the cost connection between events, otherwise the cost is considered in the beginning of activities which means simplified activities’ connection in this paper. 
Those differences lead to the different of the calculation results. The results of He (2006) is that total time of construction is 19, The Net Present Value is 779.0, each activity’ start time is {0 3 7 6 10 16 19}, each activity’ execute mode is {2 2 1 2 1 2 1 1 2 2 }, the payment happens at the event 2,4,5,7. But the results of this research are different. Total time of construction is 21, each activity’ execute mode is {1 2 1 2 1 2 1 1 2 2 }. The net present value, each activity’ actual start time and end time and payment schedule is different.

Then the analyzed of the two results are given.
 The time of constriction and each activity’ real start time is different. The total time of constriction is longer than He’. The mainly reason is that this paper does not consider the flexible resource. It means that the maximum of resources can not be changed which may reduce the possibility of activities happened at the same time. Otherwise the model of He (2006) considers the maximum of resources can be increased. It may increase the possibility of activities happened at the same time. So the total time of construction is longer in this paper. Each activity’ real start time is also affected by the maximum resources.
 Each activity’ executed mode is different. The first activity does not adopt the second’ mode in this paper. It is reasonable. From activity’ starts time, the first and second activity start and end at the same time. The third activity happens after these two activities. If the first activity adopts the second’ mode, it not only does not influence on the start time of the third activity, but also increases the cost. It is deviated from the optimization target, so there is no need for using the second execute mode. In the model of He(2006), The first activity adopts second’ mode because of the different second node. The maximum resources can be increased and the possibility of activities happened at the same time may be increased too. The first activity adopts second’ mode which may make the latter activities’ start time ahead of the schedule. So this calculation result is reasonable too.
 The net present value is different. The results are bigger than the model of He (2006). Those differences have effect on the calculation results. It can be seen from the table 4.5; Payment schedule has certain effect on the calculation results.

In a word, although the calculation results are different from the results of He (2006), through the contrast analysis, it can be seen that the different influence factors will lead to different results and the difference is reasonable and explanatory.
4.6 Summary of analysis
In this section, firstly, it introduces the principle and concept of the particle swarm algorithm and gives a detailed elaboration to variable and iteration involved in the algorithm. Then it presents the main flow chart. At last, it proves that it is feasible to solve the maximum net present value using discrete particle swarm algorithm. It provides a reference to solve this kind of problem and also gives a reference to actual project.

5. Discussions 这个和CONCLSION有问题目，老师是这样写的，具体什么意思我也不懂。
implication for other researchers(这个是理论性的谈谈)
1,Implication for Purchaser (a decision flow model to product?)
2,Implication for project managers?
Pursuing the maximum net present value has emerged in network project, especially at the broad heading—just like the case -- JZDWBD-V which has been used in this dissertation. However, there are few project announced that they let the interest maximized. The truth is known that net present value problem is still at its primary stage and it is a senior stage developed in western countries where this problem has developed very mature. So whether existing method can fit the network planning of big project and help it develop becomes a question, which is also a part of question that this dissertation tends to answer.
Network planning technique has widely applied and promoted. The optimization of network plan is the higher level of the application of network planning technique. It has become a necessary component in the project management, and is an important content of modern project management. Based on consulting the related literature of optimization of network planning, this dissertation mainly aims at maximizing NPV problem. In the course of the study, particle swarm algorithm is applied to solve the maximum net present value, and combines with the characteristics of problem; finally it uses the discrete particle swarm algorithm to solve the problem. Next there will be a summary of the study in this dissertation and the main exploratory conclusion.
 It points out that the deficiency of network planning optimization according to the current research situation of network planning optimization. Meanwhile it puts forward that the maximizing net present value gradually become the global research hot spot in network planning optimization, but in china this problem is still in the stage of exploration.
 It analyzes the previous research achievements on maximum net present value problem and try to consider various factors together, such as : resource constraints, executive mode, the owners’ payment, rewards and punishment, cash inflows and outflows, etc. Then analyzes these factors one by one and form a decision variable including activity’s sequences, activity’s executive mode and the schedule of owners’ payment.
 It studies the principle of the standard particle swarm algorithm, and labors the characteristics of discrete particle swarm algorithm according to the discrete characteristics of the decision variables in this research. Besides it obtains the maximum net present value of the given case using discrete particle swarm algorithm and gives comparative analysis on the existing results. Finally , it verifies the feasibility of the algorithm. The calculation results show that the algorithm finds a couple of the approximate solution of the optimal one. It is accordance with combinatorial optimization and gives a reference on optimization of project schedule.
 It adopts the serial generating mechanism in project generating schedule mechanism and let activities’ execution sequence as decision variable replaced the activities’ real start time. Compared with parallel generating mechanism, Serial generating mechanism would ensure the searching optimization performance of the algorithm.
 In the realization of the algorithm, according to the characteristics of problem this dissertation takes example by the successful experience on solving TSP (traveling salesman problem) by discrete particle swarm algorithm, especially on the iteration method of activities sequence, and gives the definition of the position and speed. It works out the difficulty of iterating activities sequence.

代写留学生论文6. Conclusions and Further Research
In this chapter, there are two problems to be handled. In the first place, the work finished in the research will be overviewed. Secondly, suggestions of future work following the work done here will be illustrated.
6.1 Conclusions
The purpose of this dissertation is to explore the network planning in China: how to get the maximum net present value in big project in China and whether now existing methods fits the situation of China to improve the performance of the optimal solution. The Chinese project is used as a case—JZDWBD-V is a successful network planning by now in China. Particle swarm algorithm can be viewed as a feasible method for several reasons such as algorithm finds a couple of the approximate solution of the optimal one. So the data in this case is believed to reflect the solving of net present value of network planning in China. Some means, the case selected has be used to avoid or resolve the problems such as information security. Otherwise, some other problem such as lack of experience still need time to solve.
6.2 Further research
This dissertation makes some exploratory research on the maximizing NPV problems which is an area of network planning. But there still exist many improvements.
 In the process of studying the maximum net present value, this paper makes a reference to some assumptions made by previous researchers. But I think some assumptions can be relaxed, such as nonrenewable resources, double constraint resources to be considered in the maximum net present value; Cash outflows occurs in the middle of activities, which can get more accurate net present value.
 In the solving process of adopting discrete particle swarm algorithm to a specific example, the optimization is not as better as expectations due to the complexity of the variables. Especially, the payment schedule variables cannot get a more stable solution. It can be imagined that when the scale of the problems increases, the convergence of the algorithm and searching for optimum performance need to be made further improvement.
 Flexible resource is not studied in this dissertation. It is necessary to make some improvements because flexible resource can give a further optimization on total construction period.
 It lacks the analysis of complexity during the process of coding. The efficiency needs to be improved further.

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