簡易檢索 / 詳目顯示

研究生: 史珍寧
Jenny - Sihombing
論文名稱: Prioritization of Toll Road Projects in Indonesia using Fuzzy Multiple Objective Programming
Prioritization of Toll Road Projects in Indonesia using Fuzzy Multiple Objective Programming
指導教授: 呂守陞
Sou-Sen Leu
口試委員: 楊亦東
I-Tung Yang
黃榮堯
Rong-Yau Huang
學位類別: 碩士
Master
系所名稱: 工程學院 - 營建工程系
Department of Civil and Construction Engineering
論文出版年: 2009
畢業學年度: 97
語文別: 英文
論文頁數: 138
中文關鍵詞: decision makingtoll road projectprioritizationoptimizationfuzzy MOP
外文關鍵詞: decision making, toll road project, prioritization, optimization, fuzzy MOP
相關次數: 點閱:133下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

The public project selection is strongly related to government budgeting. That is why the projects need to be well prioritized. The objective of this study is to rank the toll road projects, so it can achieve the maximum objectives of the government’s program. This study use Fuzzy Multiple Objective Programming by combining of several methods and approaches to built the optimization formula. Fuzzy, because in this study we deal with vagueness of the decision makers’perception. Multiple Objective Programming, because we want to maximize objective subject to constraints. Entropy weight method for weighting the variables, and the establishment of fuzzy rule as the constraints were done in model development. Using LINDO’s software, we can get the optimal solutions. The last, the optimal value then was used as standard in rating the projects using Project Performance Index method. This study is usefull to support the government to make decision on budget prioritization.


The public project selection is strongly related to government budgeting. That is why the projects need to be well prioritized. The objective of this study is to rank the toll road projects, so it can achieve the maximum objectives of the government’s program. This study use Fuzzy Multiple Objective Programming by combining of several methods and approaches to built the optimization formula. Fuzzy, because in this study we deal with vagueness of the decision makers’perception. Multiple Objective Programming, because we want to maximize objective subject to constraints. Entropy weight method for weighting the variables, and the establishment of fuzzy rule as the constraints were done in model development. Using LINDO’s software, we can get the optimal solutions. The last, the optimal value then was used as standard in rating the projects using Project Performance Index method. This study is usefull to support the government to make decision on budget prioritization.

Abstract Acknowledgements Table of Contents List of Figures List of Tables IIntroduction 1.1General 1.2Problem Statement 1.3Research Objectives 1.4Scope Definition 1.5Research Methodology 1.6Study Outline IIStudy and Review Related Literature 2.1Study of Public Project Selection 2.2Study of Decision Making 2.3Study of Fuzziness 2.4Summary IIIModel Development 3.1Delphi Methods 3.1.1Traditional Delphi Method 3.1.2Fuzzy Delphi Method (FDM) 3.2Multi Criteria Decision Making (MCDM) 3.2.1Multiple Attribute Decision Making (MADM) 3.2.2Multiple Objective Decision Making (MODM) 3.2.3Criterion Weight 3.2.3.1Pairwise Comparison Method 3.2.3.2Entropy Weight Method 3.3Fuzzy Logic 3.3.1Fuzzy Arithmetics 3.3.1.1Triangular Fuzzy Numbers (TFNs) 3.3.1.2Trapezoidal Fuzzy Number (TrFNs) 3.3.2Fuzzy Proposition 3.3.3Defuzzification 3.4Linear Programming 3.5Rating Methods 3.6Summary IVModel Implementation 4.1Case Study 4.1.1Overview of Toll Road Project in Indonesia 4.1.2Determining Decision Makers 4.2Building Optimization Model 4.2.1Screening Factors 4.2.2Building Objective Function 4.2.3Developing Constraints 4.2.4Optimization Model Formula 4.3Solving Optmization Problem 4.3.1Optimal Solutions 4.3.2Sensitivity Analysis 4.4Summary VResult and Comparison 5.1Analysis of Project Performance Index (PPI) 5.2Comparison with AHP Method 5.3Summary VIConclusions and Recommendations 6.1Conclusions 6.2Recommendations Appendix AProject’s Profile Appendix BEntropy Weight Appendix CCrisp Score of Linguistic Variable Appendix DOptimal Value of Variable Appendix EProject Rating Appendix FProject Ranking using AHP List of Reference Biographic Note

1.Bojadziev G. and Bojadziev M. (1997). Fuzzy Logic for Business, Finance and Management. World Scientific, London.
2.Bozbura F.T. and Beskese A (2007). “Prioritization of Organizational Capital Measurement Indicators using a Fuzzy AHP”, International Journal of Approximate Reasoning; 44: 124-147.
3.Buckley J.J. (1984): “The Multiple Judge, Multiple Criteria Ranking Problem; a Fuzzy Set Approach”, Fuzzy Sets and Systems; 13: 25-37.
4.Cebeci, U. (2009): “Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced score card”, Expert Systems with Applications; 36: 8900-8909.
5.Chang P.T., Huang L.C., and Lin H.J. (2000): “The Fuzzy Delphi Method Via Fuzzy Statistics And Membership Function Fitting And An Application To The Human Resources”, Fuzzy Set Syst; 112: 511-20.
6.Chang Y.H., Wey, W.M., and Tseng, H.Y. (2009): “Using ANP Priorities with Goal Programming for Revitalization Strategies in Historic Transport: A Case Study of the Alishan Forest Railway”, Expert Systems with Applications; 36: 8682-8690.
7.Chen, Shu-Jen and Hwang, Ching-Lai (1992). Fuzzy Multiple Attribute Decision Making: Methods and Applications. Springer-Verlag, New York.
8.Cheng, J.H., Chen, C.W., and Lee, C.Y. (2006): ”Using Fuzzy Analytical Hierarchy Process for Multi-criteria Evaluation Model of High-Yield Bonds Investment”, IEEE International Conference on Fuzzy Systems, Vancouver Canada; 0-7803-9489-5/06/$20/©IEEE.
9.Dalkey, N. and Helmer, O (1963): “An Experimental Application Of The Delphi Method To The Use Of Experts”, Management Science; 9(3): 458-67.
10.Dubois, D. and Prade, H. (1978): ”Operations on Fuzzy Numbers”, International Journal of System Science; 9(6): 613-626.
11.Costa, C.A.B., Fernandez, T.G., and Correia, P.V.D. (2006): “Prioritisation of Public Investment in Social Infrastructure using Multi criteria Value Analysis and Decision Conferencing, a Case Study”, International Transactions in Operational Research; 13: 279-297.
12.Goletsis, Y., Psarras, J., and Samouilidis. J.E. (2003): “Project Ranking in the Armenian Energy Sector using Multicriteria Method for Groups”, Annals of Operations Research; 120: 135-157.
13.Haq, A.N. and Kannan, G. (2006): “Fuzzy Analytical Hierarchy Process for Evaluating and Selecting a Vendor in a Supply Chain Model”, International Journal Advantage Manufacture Technology; 29: 826-835.
14.Ho, Y.F and Chen, H.L. (2007): “Healthy Housing Rating System”, Journal of Architecture, 60: 115-136.
15.Ho, Y.F. and Wang, H.L (2005): “Appying Fuzzy Delphi Method to Select the Variables of a Sustainable Urban System Dynamics Model”, The 23rd International Conference of System Dynamics Society, Sloan School Management, MIT, USA.
16.Huang, C.C., Chu, P.Y. and Chiang, Y.H. (2006): “A Fuzzy AHP in Government-sponsored R&D Project Selection”, The International Journal of Management Science; Omega 36: 1038-1052.
17.Hsu, H.M. and Chen, C.T (1996): “Aggregation of Fuzzy Opinions under Group Decision Making”, Fuzzy Sets and Systems; 79: 279-285.
18.Hwang, F. (1987). An Expert Decision Making Support System for Multiple Attribute Decision Making. Ph.D. Thesis, Department of Industrial Engineering, Kansas State University.
19.Hwang, C.L. and Yoon, K (1981). Multiple Attribute Decision Making, Methods and Applications: A State of The Art Survey”, Springer-Verlag, New York.
20.Ishikawa, A. and Amagasa, M. (1993): “The Max-Min Delphi Method And Fuzzy Delphi Method Via Fuzzy Integration”, Fuzzy Set System : 241-53.
21.Karnib, A. (2003): “An Approach to Elaborate Priority Orders of Water Resources Projects Based on Multi-Criteria Evaluation and Fuzzy Sets Analysis”, Journal of Water Resources Management; 18: 13-33.
22.Kaufmann, A. and Gupta, M.M. (1988). Fuzzy Mathematical Models In Engineering And Management Science. Amsterdam: North-Holland.
23.Kirkwood, Craig W. (1997): “Strategic Decision Making: Multi-objective Decision Analysis with Spreadsheets”, Belmont, California: Duxbury.
24.Klir, G.J., and Folger, T.A (1988). Fuzzy Sets, Uncertainty, and Information. Prentice-Hall International, New Jersey.
25.Leu, Sou-Sen and Lin, Wei-Ming (2000). Study of Location Selection with Fuzzy Multiple Objective Programming. M.S Thesis, Department of Construction Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.
26.Li, C.C., Fun, Y.P., and Hung, J.S. (1997): “A New Measure for Supplier Performance Evaluation”, Journal of IIE Transactions; 29: 753-758.
27.Li, Shaoyuan and Hu, Chaofang (2009): “ Satisfying Optimization Method based on Goal Programming for Fuzzy Multiple Objective Problem”, European Journal of Operational Research; 197: 675-684.
28.Linstone, H. A., and Turoff, M (2002): “The Delphi Method: Techniques and Applications”, ISBN 0-201-04294-0.
29.Ma, J., Zhang, Q., Fan, Z., Liang, J., and Zhou, D. (2001): “An Approach to Multi Attribute Decision Making Based on Preference Information on Alternatives”, Proceeding of the 34th Hawaii International Conference on System Science; Department of Information Systems, City University of Hong Kong, Kowloon Tong, Hong Kong.
30.Malczewski, J. (1999). Spatial Multi-criteria Decision Analysis. In: J-C. Thill (ed.) Multi-criteria Decision-making and Analysis: A Geographic Information Sciences Approach, New York; pp. 8-49.
31.Marks, L.A., and Dunn, E.G. (1999): “Evaluating Alternative Farming Systems: a Fuzzy MADM Approac”, Selected Paper for AAEA National Meetings, Tennesse.
32.Moghaddam, M.P., Sheikh-El-Eslam, M.K., and Jadid, S.A. (2005): “MADM Framework for Generation Expansion Planning in Small Electricity Firms”, 0-7803-9156-x/05/$20©IEEE..
33.Murray, T.J., Pipino, L.L., and Gigch, J.P (1985): “A Pilot Study of Fuzzy Set Modification of Delphi”, Human System Management; 5: 76-80.
34.Raju, K.S., and Kumar, D.N. (2006): “Ranking Irrigation Planning Alternatives using Data Envelopment Analysis”, Water Resources Management; 20: 553-566.
35.Saaty, T.L., (1980). The Analytic Hierarchy Process. McGraw Hill, New York.
36.Sanaei-Nejad, S.H., Badkoo, B., and Monajjem, S. (2006): “Using GIS for Priority Assessment of Road Construction in Kermanshah Province”, A Proceeding of Map Middle East.
37.Schaeffer, Michael (2003): “The Budget and Public Sector Performance”. Sudan Budget Workshop.
38.Schrage, L. LINDO (1991): “An Optimization Modeling System. The Scientific Press, South San Francisco, CA94080-7014.
39.Shannon, C.E and Weaver, W. (1947). The Mathematical Theory of Communication. University of Illinois Press, Urbana.
40.Starr, M.K., and Zeleny, M. (1977): “Multiple Criteria Decision Making. Amsterdam & New York; 111-128.
41.Willis, T.H., Huston, C.R., and Pohlkamp, F. (1993) Evaluation Measure of Just-In-Time Supplier Performance”, Journal of Production and Inventory Management.
42.Yeh, C.H. (2002): “A Problem-based Selection of Multi-Attribute Decision Making Methods”, International Transactions in Operational Research; 9: 169-181.
43.Yeh, C.H., and Chang, Y.H. (2008): “Modelling Subjective Evaluation for Fuzzy Group Multicriteria Decision Making”, European Journal of Operational Research; 194: 464-473.
44.Zadeh, L.A. (1965): “Fuzzy Sets, Information and Control”, 8: 338-353..
45.Technical Paper of Organization for Economic Co-operation and Development (OECD) Volume 7 No. 1 (2007): “OECD Journal on Budgeting”.
46.The Journal of Supply Chain Management (2002): “Measuring the Performance of Suppliers: An Analysis of Evaluation Precesses, Vol. 38, No.1.

QR CODE