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


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Multi-objective Optimization Genetic Algorithm Incorporating Preference Information Based on Fuzzy Logic
SHEN Xiao-ningLI TaoZHANG Min
School of Information and Control,Nanjing University of Information Science and Technology,Nanjing 210044,China
fuzzy logic multi-objective optimization genetic algorithm preference
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.


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Last Update: 2012-04-30