An evolutionary algorithm with double-level archives for multiobjective optimization

Chen, Ni and Chen, Wei-Neng and Gong, Yue-Jiao and Zhan, Zhi-Hui and Zhang, Jun and Li, Yun and Tan, Yu-Song (2015) An evolutionary algorithm with double-level archives for multiobjective optimization. IEEE Transactions on Cybernetics, 45 (9). pp. 1851-1863. ISSN 2168-2275 (https://doi.org/10.1109/TCYB.2014.2360923)

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Abstract

Existing multiobjective evolutionary algorithms (MOEAs) tackle a multiobjective problem either as a whole or as several decomposed single-objective sub-problems. Though the problem decomposition approach generally converges faster through optimizing all the sub-problems simultaneously, there are two issues not fully addressed, i.e., distribution of solutions often depends on a priori problem decomposition, and the lack of population diversity among sub-problems. In this paper, a MOEA with double-level archives is developed. The algorithm takes advantages of both the multiobjective-problem-level and the sub-problem-level approaches by introducing two types of archives, i.e., the global archive and the sub-archive. In each generation, self-reproduction with the global archive and cross-reproduction between the global archive and sub-archives both breed new individuals. The global archive and sub-archives communicate through cross-reproduction, and are updated using the reproduced individuals. Such a framework thus retains fast convergence, and at the same time handles solution distribution along Pareto front (PF) with scalability. To test the performance of the proposed algorithm, experiments are conducted on both the widely used benchmarks and a set of truly disconnected problems. The results verify that, compared with state-of-the-art MOEAs, the proposed algorithm offers competitive advantages in distance to the PF, solution coverage, and search speed.

ORCID iDs

Chen, Ni, Chen, Wei-Neng, Gong, Yue-Jiao, Zhan, Zhi-Hui, Zhang, Jun, Li, Yun ORCID logoORCID: https://orcid.org/0000-0002-6575-1839 and Tan, Yu-Song;
  • Item type:Article
    ID code:65164
    Dates:
    Date
    Event
    30 September 2015
    Published
    16 October 2014
    Published Online
    16 September 2014
    Accepted
    Notes:© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering
    Depositing user: Pure Administrator
    Date deposited:14 Aug 2018 14:34
    Last modified:12 Nov 2024 08:44
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/65164
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