DECAL : Decomposition-Based Coevolutionary Algorithm for Many-Objective Optimization

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

View graph of relations

Author(s)

  • Yu-Hui Zhang
  • Yue-Jiao Gong
  • Tian-Long Gu
  • Hua-Qiang Yuan
  • Wei Zhang
  • Jun Zhang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)27-41
Journal / PublicationIEEE Transactions on Cybernetics
Volume49
Issue number1
Early online date20 Nov 2017
StatePublished - Jan 2019

Abstract

This paper develops a decomposition-based coevolutionary algorithm for many-objective optimization, which evolves a number of subpopulations in parallel for approaching the set of Pareto optimal solutions. The many-objective problem is decomposed into a number of subproblems using a set of well-distributed weight vectors. Accordingly, each subpopulation of the algorithm is associated with a weight vector and is responsible for solving the corresponding subproblem. The exploration ability of the algorithm is improved by using a mating pool that collects elite individuals from the cooperative subpopulations for breeding the offspring. In the subsequent environmental selection, the top-ranked individuals in each subpopulation, which are appraised by aggregation functions, survive for the next iteration. Two new aggregation functions with distinct characteristics are designed in this paper to enhance the population diversity and accelerate the convergence speed. The proposed algorithm is compared with several state-of-the-art many-objective evolutionary algorithms on a large number of benchmark instances, as well as on a real-world design problem. Experimental results show that the proposed algorithm is very competitive.

Research Area(s)

  • Algorithm design and analysis, Convergence, Decomposition, diversity enhancement, evolutionary algorithm, Evolutionary computation, many-objective optimization, Pareto optimization, Sociology

Citation Format(s)

DECAL : Decomposition-Based Coevolutionary Algorithm for Many-Objective Optimization. / Zhang, Yu-Hui; Gong, Yue-Jiao; Gu, Tian-Long; Yuan, Hua-Qiang; Zhang, Wei; Kwong, Sam; Zhang, Jun.

In: IEEE Transactions on Cybernetics, Vol. 49, No. 1, 01.2019, p. 27-41.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review