Brain storm optimization algorithm for multi-objective optimization problems

  • Authors:

  • Jingqian Xue;Yali Wu;Yuhui Shi;Shi Cheng

  • Affiliations:

  • School of Automation and Information Engineering, Xi'an University of Technology, Shaanxi, China;School of Automation and Information Engineering, Xi'an University of Technology, Shaanxi, China;Dept. of Eletrical & Electronic Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, China;Dept. of Eletrical & Electronic Engineering, Xi'an Jiaotong-Liverpool University, Suzhou, China

  • Venue:
  • ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
  • Year:
  • 2012

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Abstract

In this paper, a novel multi-objective optimization algorithm based on the brainstorming process is proposed(MOBSO). In addition to the operations used in the traditional multi-objective optimization algorithm, a clustering strategy is adopted in the objective space. Two typical mutation operators, Gaussian mutation and Cauchy mutation, are utilized in the generation process independently and their performances are compared. A group of multi-objective problems with different characteristics were tested to validate the effectiveness of the proposed algorithm. Experimental results show that MOBSO is a very promising algorithm for solving multi-objective optimization problems.