A new multi-objective evolutionary algorithm for solving high complex multi-objective problems

  • Authors:

  • Kangshun Li;Xuezhi Yue;Lishan Kang;Zhangxin Chen

  • Affiliations:

  • Jiangxi University of Science and Technology, Ganzhou, China, Jiangxi Normal University, Nanchang, China and Wuhan University, Wuhan, China;Jiangxi University of Science and Technology, Ganzhou, China;Wuhan University, Wuhan, China;Southern Methodist University, Dallas, TX

  • Venue:
  • Proceedings of the 8th annual conference on Genetic and evolutionary computation
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper, a new multi-objective evolutionary algorithm for solving high complex multi-objective problems is presented based on the rule of energy minimizing and the law of entropy increasing of particle systems in phase space, Through the experiments it proves that this algorithm can quickly obtains the Pareto solutions with high precision and uniform distribution. And the results of the experiments show that this algorithm can avoid the premature phenomenon of problems better than the traditional evolutionary algorithm because it can drive all the individuals to participate in the evolving operation in each generation.