An interactive fuzzy satisficing method for multiobjective integer programming problems through genetic algorithms

This paper deals with multiobjective integer programming problems by considering fuzzy goals of the decision maker for objective functions. After determining the fuzzy goals of the decision maker, if the decision maker specifies the reference membership values, the corresponding Pareto optimal solut...

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Veröffentlicht in:1998 Second International Conference on Knowledge-Based Intelligent Engineering Systems Proceedings Jg. 1; S. 94 - 100 vol.1
Hauptverfasser: Sakawa, M., Shibano, T., Kato, K.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 1998
Schlagworte:
Decoding
Delta modulation
Fuzzy systems
Genetic algorithms
Genetic engineering
Linear programming
Minimax techniques
Optimization methods
Systems engineering and theory
ISBN:9780780343160, 0780343166
Online-Zugang:Volltext
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Zusammenfassung:This paper deals with multiobjective integer programming problems by considering fuzzy goals of the decision maker for objective functions. After determining the fuzzy goals of the decision maker, if the decision maker specifies the reference membership values, the corresponding Pareto optimal solution can be obtained by solving the augmented minimax problem which becomes an integer programming problem. For solving the problem, decoding algorithms for 0-1 programming problems are revised and ringed double strings are also introduced. Then an interactive fuzzy satisficing method is presented together with an illustrative numerical example.
ISBN:9780780343160
0780343166
DOI:10.1109/KES.1998.725832