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9783540006534

Multi-Objective Programming and Goal Programming

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  • ISBN13:

    9783540006534

  • ISBN10:

    3540006532

  • Format: Paperback
  • Copyright: 2003-04-01
  • Publisher: Springer Nature
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Supplemental Materials

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Summary

This volume constitutes the proceedings of the Fifth International Conference on Multi-Objective Programming and Goal Programming held in Nara, Japan 2002. The book is dedicated to multi-objective methods in decision making. One half of the book is devoted to theoretical aspects, covering a broad range of multi-objective methods such as multiple linear programming, fuzzy goal programming, data envelopment analysis, game theory, and dynamic programming. Readers interested in practical applications will find in the remaining parts, a variety of approaches applied in numerous fields; including production planning, logistics, marketing, and finance.

Table of Contents

PART I: Invited Papers 1(84)
Multiple Objective Combinatorial Optimization - A Tutorial
3(16)
Matthias Ehrgott, Xavier Gandibleux
1 Importance in Practice
3(1)
2 Definitions
4(1)
3 Characteristics of MOCO Problems
4(1)
4 Exact Solution Methods
5(3)
5 Heuristic Solution Methods
8(4)
6 Directions of Research and Resources
12(1)
References
13(6)
Analysis of Trends in Distance Metric Optimisation Modelling for Operational Research and Soft Computing
19(8)
D.F. Jones, M. Tamiz
1 Introduction
19(1)
2 Distance Metric Optimisation and Meta Heuristic Methods
20(1)
3 Distance Metric Optimisation and the Analytical Hierarchy Process
21(1)
4 Distance Metric Optimisation and Data Mining
22(1)
5 Some Further Observations on Goal Programming Modelling Practice
22(1)
6 Conclusions
23(1)
References
23(4)
MOP/GP Approaches to Data Mining
27(8)
Hirotaka Nakayama
1 Introduction
27(1)
2 Multisurface Method (MSM)
28(1)
3 Goal Programming Approaches to Pattern Classification
29(1)
4 Revision of MSM by MOP/GP
30(1)
5 Support Vector Machine
31(3)
6 Concluding Remarks
34(1)
References
34(1)
Computational Investigations Evidencing Multiple Objectives in Portfolio Optimization
35(10)
Ralph E. Steuer, Yue Qi
1 Introduction
35(3)
2 Different Perspectives
38(2)
3 Computational Investigations
40(2)
4 Concluding Remarks
42(1)
References
43(2)
Behavioral Aspects of Decision Analysis with Application to Public Sectors
45(12)
Hiroyuki Tamura
1 Introduction
45(1)
2 Behavioral Models to Resolve Expected Utility Paradoxes
45(4)
3 Behavioral Models to Resolve Restrictions of Additive/Utility In dependence in Consensus Formation Process
49(5)
4 Concluding Remarks
54(1)
References
54(3)
Optimization Models for Planning Future Energy Systems in Urban Areas
57(8)
Kiichiro Tsúji
1 Introduction
57(1)
2 Optimization Problems in Integrated Energy Service System
58(1)
3 Energy System Optimization for Specific Area
59(2)
4 Optimization of DHC System[5]
61(1)
5 Optimization of Electric Power Distribution Network[6]
62(1)
6 Concluding Remarks
63(1)
References
64(1)
Multiple Objective Decision Making in Past, Present, and Future
Gwo-Hshiung Tzeng
1 Introduction
65(2)
2 Fuzzy Multiple Objectives Linear Programming
67(1)
3 Fuzzy Goal Programming
67(1)
4 Fuzzy Goal and Fuzzy Constraint Programming
68(1)
5 Two Phase Approach for Solving FMOLP Problem
69(1)
6 Goal Programming with Achievement Functions
70(1)
7 Multiple Objective Programming with DEA
71(2)
8 De Novo Programming Method in MODM
73(1)
9 Summary
74(1)
References
75(2)
Dynamic Multiple Goals Optimization in Behavior Mechanism
77(8)
P.L. Yu, C.Y. Chiang Lin
1 Introduction
78(1)
2 Goal Setting and State Evaluation
79(2)
3 Charge Structures and Attention Allocation
81(1)
4 Least Resistance Principle
82(1)
5 Information Input
82(1)
6 Conclusion
83(1)
References
83(2)
PART II: General Papers - Theory 85(222)
An Example-Based Learning Approach to Multi-Objective Programming
87(6)
Masami Amano, Hiroyuki Okano
1 Introduction
87(1)
2 Our Learning Approach
88(2)
3 Numerical Experiments
90(2)
4 Concluding Remarks
92(1)
References
92(1)
Support Vector Machines using Multi Objective Programming
93(6)
Takeshi Asada, Hirotaka Nakayama
1 Principle of SVM
93(1)
2 Multi Objective Programming formulation
94(3)
3 Application to Stock Investment problem
97(1)
4 Conclusion
97(1)
References
98(1)
On the Decomposition of DEA Inefficiency
99(6)
Yao Chen, Hiroshi Monta, Joe Zhu
1 Introduction
99(1)
2 Scale and Congestion Components
100(4)
3 Conclusion
104(1)
References
104(1)
An Approach for Determining DEA Efficiency Bounds
105(6)
Yao Chen, Hiroshi Morita, Joe Zhu
1 Introduction
105(1)
2 Determination of the Lower Bounds
106(4)
References
110(1)
An Extended Approach of Multicriteria Optimization for MODM Problems
111(6)
Hua-Kai Chiou, Gwo-Hshiung Tzeng
1 Introduction
111(1)
2 The Multicriteria Metric for Compromise Ranking Methods
112(1)
3 The Extended Compromise Ranking Approach
113(1)
4 Illustrative Example
114(2)
5 Conclusion
116(1)
References
116(1)
The Method of Elastic Constraints for Multiobjective Combinatorial Optimization and its Application in Airline Crew Scheduling
117(6)
Matthias Ehrgott, David M. Ryan
1 Multiobjective Combinatorial Optimization
117(1)
2 The Method of Elastic Constraints
118(1)
3 Bicriteria Airline Crew Scheduling: Cost and Robustness
119(2)
4 Numerical Results
121(1)
5 Conclusion
121(1)
References
122(1)
Some Evaluations Based on DEA with Interval Data
123(6)
Tomoe Entani, Hideo Tanaka
1 Introduction
123(1)
2 Relative Efficiency Value
124(1)
3 Approximations of Relative Efficiency Value with Interval Data
125(2)
4 Numerical Example
127(1)
5 Conclusion
127(1)
References
128(1)
Possibility and Necessity Measures in Dominance-based Rough Set Approach
129(6)
Salvatore Greco, Masahiro Inuiguchi, Roman Slowinski
1 Introduction
129(1)
2 Possibility and Necessity Measures
130(2)
3 Approximations by Means of Fuzzy Dominance Relations
132(2)
4 Conclusion
134(1)
References
134(1)
Simplex Coding Genetic Algorithm for the Global Optimization of Nonlinear Functions
135(6)
Abdel-Rahman Hedar, Masao Fukushima
1 Introduction
135(1)
2 Description of SCCA
136(2)
3 Experimental Results
138(1)
4 Conclusion
139(1)
References
140(1)
On Minimax and Maximin Values in Multicriteria Games
141(6)
Masakazu Higuchi, Tamaki Tanaka
1 Introduction
141(1)
2 Multicriteria Two-person Zero-sum Game
141(3)
3 Coincidence Condition
144(2)
References
146(1)
Backtrack Beam Search for Multiobjective Scheduling Problem
Naoya Honda
1 Introduction
147(1)
2 Problem Formulation
148(1)
3 Search Method
148(3)
4 Numerical Experiments
151(1)
5 Conclusion
152(1)
References
152(1)
Cones to Aid Decision Making in Multicriteria Programming
153(6)
Brian J. Hunt, Margaret M. Wiecek
1 Introduction
153(1)
2 Problem Formulation
154(1)
3 Pointed and Non-Pointed Cones in Multicriteria Programming
154(2)
4 Decision Making with Polyhedral Cones
156(1)
5 Example
157(1)
6 Conclusion
158(1)
References
158(1)
Efficiency in Solution Generation Based on Extreme Ray Generation Method for Multiple Objective Linear Programming ..
159(6)
Masaaki Ida
1 Introduction
159(1)
2 Cone Representation and Efficiency Test
160(1)
3 Efficient Solution Generation Algorithm
161(2)
4 Numerical Example
163(1)
5 Conclusion
164(1)
References
164(1)
Robust Efficient Basis of Interval Multiple Criteria and Multiple Constraint Level Linear Programming
165(6)
Masaaki Ida
1 Introduction
165(1)
2 Multiple Criteria and Multiple Constraint Level Linear Programming
166(1)
3 Interval Coefficient Problem
167(1)
4 Main Results
168(1)
5 Conclusion
169(1)
References
169(2)
An Interactive Satisficing Method through the Variance Minimization Model for Fuzzy Random Multiobjective Linear Programming Problems
171(6)
Hideki Katagiri, Masatoshi Sakawa, Shuuji Ohsaki
1 Introduction
171(1)
2 Formulation
172(2)
3 Interactive Decision Making Using the Variance Minimization Model Based on a Possibility Measure
174(2)
4 Conclusion
176(1)
References
176(1)
On Saddle Points of Multiob jective Functions
177(6)
Kenji Kimura, El Mostafa Kalmoun, Tamaki Tanaka
1 Introduction
177(1)
2 Preliminary and Terminology
177(1)
3 Existence Results of Cone Saddle Points
178(3)
References
181(2)
An Application of Fuzzy Multiobjective Programming to Fuzzy AHP
183(8)
Hiroaki Kuwano
1 Introduction
183(1)
2 Preliminaries
184(1)
3 Subjective Evaluation
185(2)
4 A Numerical Example
187(1)
5 Conclusions
188(1)
References
189(2)
On Affine Vector Variational Inequality
191(6)
Gue Myung Lee, Kwang Baik Lee
1 Introduction and Preliminaries
191(1)
2 Main Result
192(2)
References
194(3)
Graphical Illustration of Pareto Optimal Solutions
197(6)
Kaisa Miettinen
1 Introduction
197(1)
2 Graphical Illustration
198(3)
3 Discussion
201(1)
4 Conclusions
201(1)
References
202(1)
An Efficiency Evaluation Model for Company System Organization
203(6)
Takashi Namatame, Hiroaki Tanimoto, Toshikazu Yamaguchi
1 Introduction
203(1)
2 Characteristics of the Company System Organization
203(1)
3 Evaluation Model
204(3)
4 Example
207(1)
5 Conclusion
208(1)
References
208(1)
Stackelberg Solutions to Two-Level Linear Programming Problems with Random Variable Coefficients
209(6)
Ichiro Nishizaki, Masatoshi Sakawa, Kosure Kato, Hideki Katagiri
1 Introduction
209(1)
2 Two-level Linear Programming Problems with Random Variable Coefficients
209(4)
3 A Numerical Example
213(1)
References
214(1)
On Inherited Properties for Vector-Valued Multifunctions
215(6)
Shogo Nishizawa, Tamaki Tanaks, Pando Gr. Georgiev
1 Introduction
215(1)
2 Inherited Properties of Convexity
216(2)
3 Inherited Properties of Semicontinuity
218(1)
4 Conclusions
219(1)
References
220(1)
Multicriteria Expansion of a Competence Set Using Genetic Algorithm
221(6)
Serafim Opricovic, Gwo-Hshiung Tzeng
1 Introduction
221(1)
2 Multicriteria Expansion of a Competence Set
222(1)
3 Multicriteria Genetic Algorithm
222(2)
4 Illustrative Example
224(2)
5 Conclusion
226(1)
References
226(1)
Comparing DEA and MCDM Method
227(6)
Serafim Opricovic, Gwo-Hshiung Tzeng
1 Introduction
227(1)
2 Comparison of DEA and VIKOR
228(2)
3 Numerical Experiment
230(2)
4 Conclusions
232(1)
References
232(1)
Linear Coordination Method for Multi-Objective Problems
233(6)
Busaba Phruksaphanrat, Ario Ohsato
1 Introduction
233(1)
2 Lexicographic Models
234(1)
3 Efficient Linear Coordination Method Based on Convex Cone Concept
235(1)
4 Numerical Example
235(3)
5 Conclusions
238(1)
References
238(1)
Experimental Analysis for Rational Decision Making by Aspiration Level AHP
239(6)
Kouichi Taji, Junsuke Suzuki, Satoru Takahashi, Hiroyuki Tamura
1 Introduction
239(1)
2 Irrational Ranking
240(1)
3 Cause and Several Revisions
241(1)
4 Experimental Analysis
242(2)
5 Conclusion
244(1)
References
244(1)
Choquet Integral Type DEA
245(6)
Eiichiro Takahagi
1 Introduction
245(1)
2 Fuzzy Measure Choquet Integral Model
245(1)
3 CCR Model (Notations)
246(1)
4 Choquet Integral Type DEA (Maximum Model)
246(1)
5 Choquet Integral Type DEA(Average Model)
247(1)
6 Numerical Examples
248(2)
7 Conclusions
250(1)
References
250(1)
Interactive Procedures in Hierarchical Dynamic Goal Programming
251(6)
T. Trzaskalik
1 Discrete Multi-Objective Dynamic Programming Problem
251(1)
2 Goal Programming Approach
252(1)
3 Hierarchical Goal Programming Approach
253(1)
4 Numerical Example
254(2)
References
256(1)
Solution Concepts for Coalitional Games in Constructing Networks
257(6)
Masayo Tsurumi, Tetsuzo Tanino, Masahiro Inuiguchi
1 Introduction
257(1)
2 Games in Constructing Networks
258(1)
3 Conventional Solution Concepts
259(2)
4 A New Concept of Demand Operations
261(1)
5 Conclusion
262(1)
References
262(1)
Multi-Objective Facility Location Problems in Competitive Environments
263(6)
Takeshi Uno, Hiroaki Ishii, Seiji Saito, Shigehiro Osumi
1 Introduction
263(1)
2 Medianid Problem with Single Objective
264(1)
3 Medianid Problem with Multi-Objective
265(1)
4 Algorithm for Competitive Facility Location Problems
266(1)
5 Numerical Experiments
266(2)
6 Conclusions
268(1)
References
268(1)
Solving Portfolio Problems Based on Meta-Controled Boltzmann Machine
269(6)
Junzo Watada, Teruyuki Watanabe
1 Introduction
269(1)
2 Portfolio Selection Problem
270(1)
3 Energy Functions for Meta-controlled Boltzmann Machine
270(2)
4 Numerical Example
272(1)
5 Concluding Remarks
273(1)
References
273(2)
Tradeoff Directions and Dominance Sets
275(6)
Petra Weidner
1 Introduction
275(1)
2 Tradeoff Concepts
276(2)
3 A Scalarization Using Widened Dominance Sets
278(1)
4 Calculation of Tradeoffs
279(1)
References
280(1)
A Soft Margin Algorithm Controlling Tolerance Directly
281(8)
Min Yoon, Hirotaka Nakayama, Yeboon Yun
1 Introduction
281(1)
2 Error Bound for Soft Margin Algorithms
281(2)
3 The Proposed Method
283(2)
4 Conclusion
285(1)
References
286(3)
An Analysis of Expected Utility Based on Fuzzy Interval Data
289(6)
Shin-ichi Yoshikawa, Tetsúji Okuda
1 Introduction
289(1)
2 Fuzzy Interval Data and Membership Functions
290(1)
3 Expected Utility Using Fuzzy Interval Data
290(1)
4 The Value of Fuzzy Information
291(1)
5 The Amount of Fuzzy Information μ
292(1)
6 Numerical Example
293(1)
7 Conclusions
294(1)
On Analyzing the Stability of Discrete Descriptor Systems via Generalized Lyapunov Equations
295(6)
Qingling Zhang, James Lam, Ligian Zhang
1 Introduction
295(1)
2 Preliminaries
296(2)
3 Asymptotic Stability
298(2)
References
300(1)
Solving DEA via Excel
301(6)
Joe Zhu
1 Introduction
301(1)
2 DEA Spreadsheets
302(4)
3 Conclusions
306(1)
References
306(1)
PART III: General Papers - Applications 307
Planning and Scheduling Staff Duties by Goal Programming
309(8)
Sydney CK Chu, Christina SY Yuen
1 Introduction
309(2)
2 Goal Programming Models
311(3)
3 A Concluding Remark
314(1)
References
315(2)
An Interactive Approach to Fuzzy-based Robust Design
317(8)
Hideo Fújimoto, Yu Tao, Satoko Yamakawa
1 Introduction
317(1)
2 Proposed Approach
318(3)
3 Pressure Vessel Design Problem
321(2)
4 Conclusions
323(1)
References
324(1)
A Hybrid Genetic Algorithm for solving a capacity Constrained Truckload Transportation with crashed customer
325(8)
Sangheon Han, Yoshio Tabata
1 Introduction
325(1)
2 The Vehicle Routing Problem; The Case of Crashed Customers
326(2)
3 A hybrid methodology for Vehicle Routing Problem
328(2)
4 Numerical Example and Discussions
330(1)
5 Conclusions and Recommendations
330(1)
References
331(2)
A Multi-Objective Programming Approach for Evaluating Agri-Environmental Policy
333(6)
Kiyotada Hayashi
1 Introduction
333(1)
2 Mathematical Programming Approach to Agri-Environmental Problems
334(1)
3 Possibility of Integrated Evaluation
335(2)
4 Concluding Remarks
337(1)
References
338(1)
Improve the Shipping Performance of Build-to-ORder (BTO) Product in Semiconductor Wafer Manufacturing
339(8)
Shao-Chung Hsu, Chen-Yuan Peng, Chia-Hung Wu
1 Introduction
339(2)
2 The Yield Forecast Model
341(1)
3 Computational Simulation
342(1)
4 An Empirical Case and the Application
343(1)
5 Conclusion and Future Work
344(1)
References
345(2)
Competence Set Expansion for Obtaining Scheduling Plans in Intelligent Transportation Security Systems
347(6)
Yi-Chung Hu, Yu-Jing Chiu, Chin-Mi Chen, Gwo-Hshiung Tzeng
1 Introduction
347(1)
2 Competence Set Expansion
348(1)
3 A Relationship-Based Method
349(1)
4 Generate Learning Sequences
350(1)
5 Empirical Results
351(1)
6 Conclusions
351(1)
References
352(1)
DEA for Evaluating the Current-period and Cross-period Efficiency of Taiwan's Upgraded Technical Institutes
353(8)
Li-Chen Liu, Chuan Lee, Gwo-Hshiung Tzeng
1 Introduction
353(1)
2 The Selection of School Objects and Variables for Performance Evaluation
354(1)
3 Building the Performance Model
355(2)
4 Emperical Study: Taiwan's 38 Upgraded Technical Institutes
357(2)
5 Conclusions
359(1)
References
359(2)
Using DEA of REM and EAM for Efficiency Assessment of Technology Institutes Upgraded from Junior Colleges: The Case in Taiwan
361(6)
Li-Chen Liu, Chuan Lee, Gwo-Hshiung Tzeng
1 Introduction
361(1)
2 Selection of Variables and Samples for Efficiency Assessment
362(1)
3 Measure of Assessment Model
362(3)
4 Analysis and Conclusion for the Results of Case Study
365(1)
5 Conclusions
366(1)
References
366(1)
The Comprehensive Financial Risk Management in a Bank - Stochastic Goal Programming Optimization
367(6)
Jerzy Michnik
1 Introduction
367(1)
2 Model Formulation
368(3)
3 The Exemplary Model and Computational Tests
371(1)
4 Conclusions
372(1)
References
372(1)
The Effectiveness of the Balanced Scorecard Framework for E-Commerce
373(8)
Jamshed J. Mistry, B.K. Pathak
1 Introduction
373(1)
2 Background and Significance
374(1)
3 Methodology
375(1)
4 Results
376(3)
References
379(2)
A Study of Variance of Locational Price in a Deregulated Generation Market
381(8)
Jin-Tang Peng, Chen-Fu Chien
1 Introduction
381(1)
2 Proposed Market Mechanism
382(2)
3 Scenario and Simulation Analysis
384(2)
4 Discussion and Conclusion
386(1)
References
386(3)
Pseudo-Criterion Approaches to Evaluating Alternatives in Mangrove Forests Management
389(6)
Santha Chenayah Ramu, Eiji Takela
1 Introduction
389(1)
2 Ternary Comparison Method (TCM)
390(1)
3 Pseudo-Criterion Approaches to Mangrove Forests Management
390(4)
4 Concluding Remarks
394(1)
References
394(1)
Energy-Environment-Cost Tradeoffs in Planning Energy Systems for an Urban Area
395(8)
Hideharu Sugihara, Kiichiro Tsuji
1 Introduction
395(1)
2 Definitions of Energy System Alternatives
395(2)
3 Formulation of Multi-objective Optimization Model
397(2)
4 Tradeoff Analyses
399(1)
5 Conclusion
400(1)
Reference
400(3)
DEA Approach to the Allocation of Various TV Commercials to Dayparts
403(6)
Katsuaki Tanaka, Eiji Takeda
1 Introduction
403(1)
2 DEA Approach to the Allocation of Various TV Commercials to Dayparts
404(2)
3 Concluding Remarks
406(1)
References
406(3)
Analyzing Alternative Strategies of Semiconductor Final Test
409(6)
Hung-Ju Wang, Chen-Fu Chien, Chung-Jen Kuo
1 Introduction
409(1)
2 Research Framework
409(2)
3 An Empirical Study
411(3)
4 Conclusion
414(1)
References
414(1)
A Discrete-Time European Options Model under Uncertainty in Financial Engineering
415(6)
Yuji Yoshida
1 Introduction
415(1)
2 Fuzzy Stochastic Processes
416(1)
3 European Options in Uncertain Environment
416(3)
4 The Expected Price of European Options
419(1)
References
420(1)
Multipurpose Decision-Making in House Plan by Using AHP
421
Bingjiang Zhang, Hui Liang, Tamaki Tanaka
1 Introduction
421(1)
2 Housing Planing Model by AHP
421(2)
3 Comprehensive Evaluation for the House of Room Arrangements
423(2)
4 Algorithm
425(1)
5 Conclusion and Remarks
426(1)
References
426

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