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Fuzzy preference-based multi-objective optimization method

Fuzzy preference-based multi-objective optimization method Multiobjective evolutionary computation is still quite young and there are many open research problems. This paper is an attempt to design a hybridized Multiobjective Evolutionary Optimization Algorithm with fuzzy logic called Fuzzy Preference-Based Multi–Objective Optimization Method (FPMOM). FPMOM as an integrated components of Multiobjective Optimization Technique, Evolutionary Algorithm and Fuzzy Inference System able to search and filter the pareto-optimal and provide a good trade-off solution for the multiobjective problem using fuzzy inference method to choose the user intuitive based specific trade-off requirement. This paper will provide a new insight into the behaviourism of interactive Multiobjective Evolutionary Algorithm optimization problems using fuzzy inference method. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence Review Springer Journals

Fuzzy preference-based multi-objective optimization method

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References (6)

Publisher
Springer Journals
Copyright
Copyright © 2011 by Springer Science+Business Media B.V.
Subject
Computer Science; Artificial Intelligence (incl. Robotics); Computer Science, general
ISSN
0269-2821
eISSN
1573-7462
DOI
10.1007/s10462-011-9264-4
Publisher site
See Article on Publisher Site

Abstract

Multiobjective evolutionary computation is still quite young and there are many open research problems. This paper is an attempt to design a hybridized Multiobjective Evolutionary Optimization Algorithm with fuzzy logic called Fuzzy Preference-Based Multi–Objective Optimization Method (FPMOM). FPMOM as an integrated components of Multiobjective Optimization Technique, Evolutionary Algorithm and Fuzzy Inference System able to search and filter the pareto-optimal and provide a good trade-off solution for the multiobjective problem using fuzzy inference method to choose the user intuitive based specific trade-off requirement. This paper will provide a new insight into the behaviourism of interactive Multiobjective Evolutionary Algorithm optimization problems using fuzzy inference method.

Journal

Artificial Intelligence ReviewSpringer Journals

Published: Jun 2, 2011

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