臺灣博碩士論文加值系統

Nowadays, the minimization of project time and cost is an important issue. However, time and cost problems are difficult to solve. They are affected by the uncertain factor. Then, the construction project always fails to achieve the effectiveness of time and cost performance. It causes delays and cost overrun. Over the past few years, the Earned Value Method (EVM) is used for forecasting project time and cost. However, its method does not consider uncertainties. In this research, SOS-NN-LSTM is required to establish the ESTC and ECTC prediction model based on time now performance. Then, the prediction model will be integrated with MOSOS to obtain the optimal prediction value. The integration is needed because there is no direct equation to calculate the ESTC and ECTC. The Pareto curve identified based on the prediction values of MOSOS. The Pareto curve is used to determine the optimal trade-off between project duration and project cost. Then, the indifference curve is used to solve the trade-off problem between ESTC and ECTC which give the decision-maker preference.

Nowadays, the minimization of project time and cost is an important issue. However, time and cost problems are difficult to solve. They are affected by the uncertain factor. Then, the construction project always fails to achieve the effectiveness of time and cost performance. It causes delays and cost overrun. Over the past few years, the Earned Value Method (EVM) is used for forecasting project time and cost. However, its method does not consider uncertainties. In this research, SOS-NN-LSTM is required to establish the ESTC and ECTC prediction model based on time now performance. Then, the prediction model will be integrated with MOSOS to obtain the optimal prediction value. The integration is needed because there is no direct equation to calculate the ESTC and ECTC. The Pareto curve identified based on the prediction values of MOSOS. The Pareto curve is used to determine the optimal trade-off between project duration and project cost. Then, the indifference curve is used to solve the trade-off problem between ESTC and ECTC which give the decision-maker preference.

ABSTRACT V
ACKNOWLEDGEMENT VI
TABLES OF CONTENTS IX
LIST OF FIGURES XI
LIST OF TABLES XIII
ABBREVIATIONS AND SYMBOLS XIV
CHAPTER 1: INTRODUCTION 1
1.1 RESEARCH MOTIVATION 1
1.2 RESEARCH OBJECTIVE 4
1.3 DETERMINE SCOPE OF STUDY 4
1.4 RESEARCH METHODOLOGY 5
1.4.1 Identify the problems 7
1.4.2 Review of Literature 8
1.4.3 Model Construction 8
1.4.4 Model Validation and Application 9
1.4.5 Conclusion and Recommendation 9
1.5 STUDY OUTLINE 10
CHAPTER 2: LITERATURE REVIEW 11
2.1 EARNED VALUE METHOD (EVM) 11
2.2 SYMBIOTIC ORGANISMS SEARCH - NEURAL NETWORK - LONG SHORT-TERM MEMORY (SOS-NN-LSTM) 13
2.3 MULTI OBJECTIVE SYMBIOTIC ORGANISMS SEARCH (MOSOS) 18
2.4 INDIFFERENCE CURVE (IC) 22
CHAPTER 3: MODEL CONSTRUCTION 23
3.1 PHASE 1: PREDICTION MODEL TRAINING 25
3.2 PHASE 2: SCHEDULE AND COST TRADE-OFF OPTIMIZATION MODEL 25
3.3 PHASE 3: THE MANAGEMENT STRATEGY FOR SCHEDULE AND COST TRADE-OFF 30
CHAPTER 4: MANAGEMENT STRATEGY FOR PROJECT TIME AND COST 37
4.1 PROJECT INFORMATION 37
4.1.1 Data Collection 38
4.1.2 Selection ESTC and ECTC Influence Factors 40
4.2 THE RESULT OF TRAINING MODEL BY SOS-NN-LSTM 44
4.2.1 SOS-NN-LSTM Performance Result for ESTC 44
4.2.2 SOS-NN-LSTM Performance Result for ECTC 45
4.3 THE RESULT OF TIME AND COST TRADE-OFF BY MOSOS 47
4.4 MANAGEMENT STRATEGY OF TIME/COST TRADE-OFF USING INDIFFERENCE CURVE 47
4.4.1 Case Study 48
4.4.2 Time and Cost Preference Function 52
4.4.3 The Tangent Point of Pareto Curve and Indifference Curve 55
4.4.4 The Calculation of ESAC 56
4.4.5 The Calculation of ECAC 58
4.4.6 Management Strategy Development 60
4.4.7 Penalty 62
CHAPTER 5: CONCLUSIONS 65
5.1 CONCLUSIONS 65
5.2 RECOMMENDATION FOR FURTHER STUDY 67
REFERENCES 68
APPENDIX 71

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