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Published in:
2013 | OriginalPaper | Chapter
Practically Desirable Solutions Search on Multi-Objective Optimization
Authors : Natsuki Kusuno, Hernán Aguirre, Kiyoshi Tanaka, Masataka Koishi
Published in: Learning and Intelligent Optimization
Publisher: Springer Berlin Heidelberg
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Abstract
This work investigates a method to search practically desirable solutions expanding the objective space with additional fitness functions associated to particular decision variables. The aim is to find solutions around preferred values of the chosen variables while searching for optimal solutions in the original objective space. Solutions to be practically desirable are constrained to be within a certain distance from the instantaneous Pareto optimal set computed in the original objective space. Our experimental results show that the proposed method can effectively find practically desirable solutions.