Two Arch2: An Improved Two-Archive Algorithm for Many-Objective Optimization

Handing WANG, Licheng JIAO, Xin YAO

Research output: Journal PublicationsJournal Article (refereed)peer-review

428 Citations (Scopus)

Abstract

Many-objective optimization problems (ManyOPs) refer, usually, to those multiobjective problems (MOPs) with more than three objectives. Their large numbers of objectives pose challenges to multiobjective evolutionary algorithms (MOEAs) in terms of convergence, diversity, and complexity. Most existing MOEAs can only perform well in one of those three aspects. In view of this, we aim to design a more balanced MOEA on ManyOPs in all three aspects at the same time. Among the existing MOEAs, the two-archive algorithm (Two-Arch) is a low-complexity algorithm with two archives focusing on convergence and diversity separately. Inspired by the idea of Two-Arch, we propose a significantly improved two-archive algorithm (i.e., Two-Arch2) for ManyOPs in this paper. In our Two-Arch2, we assign different selection principles (indicator-based and Pareto-based) to the two archives. In addition, we design a new Lp-norm-based ( p<1) diversity maintenance scheme for ManyOPs in Two-Arch2. In order to evaluate the performance of Two-Arch2 on ManyOPs, we have compared it with several MOEAs on a wide range of benchmark problems with different numbers of objectives. The experimental results show that Two Arch2 can cope with ManyOPs (up to 20 objectives) with satisfactory convergence, diversity, and complexity. © 1997-2012 IEEE.
Original languageEnglish
Article number6883177
Pages (from-to)524-541
Number of pages18
JournalIEEE Transactions on Evolutionary Computation
Volume19
Issue number4
Early online date26 Aug 2014
DOIs
Publication statusPublished - Aug 2015
Externally publishedYes

Keywords

  • Evolutionary algorithm
  • Lp-norm
  • manyobjective optimization
  • two-archive algorithm (Two-Arch)

Fingerprint

Dive into the research topics of 'Two Arch2: An Improved Two-Archive Algorithm for Many-Objective Optimization'. Together they form a unique fingerprint.

Cite this