Summary: | 碩士 === 國立清華大學 === 工業工程與工程管理學系 === 89 === ABSTRACT
This paper proposes a hierarchical procedure for solving multiple objective decision problems in which only partial information is given in the decision process. The procedure consists of two levels, a top-level and a base-level. The main idea is that the top-level provides partial preference information to reduce the non-dominated solution set;then the base-level determines a compromise solution from the reduced set. Furthermore, we also derive a procedure to find the tolerance regions of cost coefficients or RHS such that either the compromise solution or the final extreme solution set will maintain.
In this study we also consider that when DM is fuzzy about the tradeoff questions so that the DM may not be able to make exact tradeoffs among the objectives or sometimes, in a maximization (minimization) problem there exists some objectives for which DM may state to achieve substantially more (less) than or equal to some values. In such cases, we consider a fuzzy programming structure and construct an interactive fuzzy programming to find a satisfactory solution.
CHAPTER 2 LITERATURE REVIEW . . . . 5
CHAPTER 3 MULTI-OBJECTIVE ANALYSIS WITH PARTIAL
PREFERENCE INFORMATION . . . 8
3.1 Preference Presentation . . . . 8
3.2 Properties Derived From the Partial Information . 10
3.3 Conclusion . . . . . 12
CHAPTER 4 THE INTERACTIVE PROCEDURE FOR HIERARCHICAL DECISION
MAKING . . . . . 13
4.1 The Zionts-Wallenius Algorithm . . . 13
4.2 The Interactive Procedure for Hierarchical Decision
Makers . . . . . 14
4.3 Conclusion . . . . . 23
CHAPTER 5 TOLERANCE ANALYSIS OF AN MOLP WITH HIERARCHICAL
DECISION MAKERS . . . . 25
5.1 The Revised Algorithm for Perturbation Analysis . 35
5.2 Tolerance Analysis of the Cost Coefficients for
Hierarchical Decision Makers . . . 43
5.3 Tolerance Analysis of the RHS . . . 52
5.4 Tolerance Analysis of Both the Cost Coefficients
and RHS . . . . . 53
5.5 Conclusion . . . . . 54
CHAPTER 6 INTERACTIVE FUZZY PROGRAMMING . . 55
6.1 Problem Formulation . . . . 55
6.2 An Interactive Fuzzy Programming for Hierarchical
Decision Makers . . . . 58
6.3 Conclusion . . . . . 64
CHAPTER 7 SUMMARY AND CONCLUSIONS . . . 65
REFERENCES . . . . . 67
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