English

A New Repair Operator for Multi-objective Evolutionary Algorithm in Constrained Optimization Problems

Neural and Evolutionary Computing 2015-04-02 v1

Abstract

In this paper, we design a set of multi-objective constrained optimization problems (MCOPs) and propose a new repair operator to address them. The proposed repair operator is used to fix the solutions that violate the box constraints. More specifically, it employs a reversed correction strategy that can effectively avoid the population falling into local optimum. In addition, we integrate the proposed repair operator into two classical multi-objective evolutionary algorithms MOEA/D and NSGA-II. The proposed repair operator is compared with other two kinds of commonly used repair operators on benchmark problems CTPs and MCOPs. The experiment results demonstrate that our proposed approach is very effective in terms of convergence and diversity.

Keywords

Cite

@article{arxiv.1504.00154,
  title  = {A New Repair Operator for Multi-objective Evolutionary Algorithm in Constrained Optimization Problems},
  author = {Zhun Fan and Wenji Li and Xinye Cai and Huibiao Lin and Shuxiang Xie and Erik Goodman},
  journal= {arXiv preprint arXiv:1504.00154},
  year   = {2015}
}

Comments

8 pages

R2 v1 2026-06-22T09:07:46.772Z