DocumentCode :
9033
Title :
MOMMOP: Multiobjective Optimization for Locating Multiple Optimal Solutions of Multimodal Optimization Problems
Author :
Yong Wang ; Han-Xiong Li ; Yen, Gary G. ; Wu Song
Author_Institution :
Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
Volume :
45
Issue :
4
fYear :
2015
fDate :
Apr-15
Firstpage :
830
Lastpage :
843
Abstract :
In the field of evolutionary computation, there has been a growing interest in applying evolutionary algorithms to solve multimodal optimization problems (MMOPs). Due to the fact that an MMOP involves multiple optimal solutions, many niching methods have been suggested and incorporated into evolutionary algorithms for locating such optimal solutions in a single run. In this paper, we propose a novel transformation technique based on multiobjective optimization for MMOPs, called MOMMOP. MOMMOP transforms an MMOP into a multiobjective optimization problem with two conflicting objectives. After the above transformation, all the optimal solutions of an MMOP become the Pareto optimal solutions of the transformed problem. Thus, multiobjective evolutionary algorithms can be readily applied to find a set of representative Pareto optimal solutions of the transformed problem, and as a result, multiple optimal solutions of the original MMOP could also be simultaneously located in a single run. In principle, MOMMOP is an implicit niching method. In this paper, we also discuss two issues in MOMMOP and introduce two new comparison criteria. MOMMOP has been used to solve 20 multimodal benchmark test functions, after combining with nondominated sorting and differential evolution. Systematic experiments have indicated that MOMMOP outperforms a number of methods for multimodal optimization, including four recent methods at the 2013 IEEE Congress on Evolutionary Computation, four state-of-the-art single-objective optimization based methods, and two well-known multiobjective optimization based approaches.
Keywords :
Pareto optimisation; evolutionary computation; sorting; MOMMOP; Pareto optimal solutions; differential evolution; evolutionary computation; implicit niching method; multimodal benchmark test functions; multimodal optimization problems; multiobjective evolutionary algorithms; multiobjective optimization problem; multiple optimal solution location; nondominated sorting; single-objective optimization based methods; transformation technique; Educational institutions; Evolutionary computation; Pareto optimization; Sociology; Vectors; Evolutionary algorithms; multimodal optimization problems; multiobjective optimization; multiple optimal solutions; transformation technique;
fLanguage :
English
Journal_Title :
Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
2168-2267
Type :
jour
DOI :
10.1109/TCYB.2014.2337117
Filename :
6870442
Link To Document :
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