Multi-Objective Optimization Based on Brain Storm Optimization Algorithm

In recent years, many evolutionary algorithms and population-based algorithms have been developed for solving multi-objective optimization problems. In this paper, the authors propose a new multi-objective brain storm optimization algorithm in which the clustering strategy is applied in the objectiv...

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Bibliographic Details
Published in:International journal of swarm intelligence research Vol. 4; no. 3; pp. 1 - 21
Main Authors: Shi, Yuhui, Xue, Jingqian, Wu, Yali
Format: Journal Article
Language:English
Published: Hershey IGI Global 01.07.2013
Subjects:
Algorithms
Clustering
Evolutionary algorithms
Multiple objective analysis
Optimization
Solution space
ISSN:1947-9263, 1947-9271
Online Access:Get full text
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Summary:In recent years, many evolutionary algorithms and population-based algorithms have been developed for solving multi-objective optimization problems. In this paper, the authors propose a new multi-objective brain storm optimization algorithm in which the clustering strategy is applied in the objective space instead of in the solution space in the original brain storm optimization algorithm for solving single objective optimization problems. Two versions of multi-objective brain storm optimization algorithm with different characteristics of diverging operation were tested to validate the usefulness and effectiveness of the proposed algorithm. Experimental results show that the proposed multi-objective brain storm optimization algorithm is a very promising algorithm, at least for solving these tested multi-objective optimization problems.
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ISSN:1947-9263
1947-9271
DOI:10.4018/ijsir.2013070101