|Table of Contents|

Multi-objective Optimization Genetic Algorithm Incorporating Preference Information Based on Fuzzy Logic

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2011年02期
Page:
245-251
Research Field:
Publishing date:

Info

Title:
Multi-objective Optimization Genetic Algorithm Incorporating Preference Information Based on Fuzzy Logic
Author(s):
SHEN Xiao-ningLI TaoZHANG Min
School of Information and Control,Nanjing University of Information Science and Technology,Nanjing 210044,China
Keywords:
fuzzy logic multi-objective optimization genetic algorithm preference
PACS:
TP18
DOI:
-
Abstract:
In order to solve the difficulty for users to select from many non-dominated solutions in multi-objective optimization,a multi-objective genetic algorithm incorporating preference information of the decision maker interactively is proposed.The algorithm makes use of a new nine-scale evaluation method to convert the linguistic preferences expressed by the decision maker to importance factors of objectives.A new outranking relation called "strength superior" which is based on the preference information is constructed via a fuzzy inference system to compare individuals instead of the commonly used "Pareto dominance" relation.The computational complexity of the algorithm is analyzed theoretically,and its ability to handle preference information is validated through simulation.Comparisons to two classical multi-objective genetic algorithms indicate that the proposed algorithm can search better solutions.

References:

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Last Update: 2012-04-30