Multimodal estimation of distribution algorithms

Yang, Qiang and Chen, Wei-Neng and Li, Yun and Chen, C. L. Philip and Xu, Xiang-Min and Zhang, Jun (2016) Multimodal estimation of distribution algorithms. IEEE Transactions on Cybernetics, 47 (3). pp. 636-650. 7407318. ISSN 2168-2275 (https://doi.org/10.1109/TCYB.2016.2523000)

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Abstract

Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for crowding and speciation, two versions of this algorithm are developed, which operate at the niche level. Then these two algorithms are equipped with three distinctive techniques: 1) a dynamic cluster sizing strategy; 2) an alternative utilization of Gaussian and Cauchy distributions to generate offspring; and 3) an adaptive local search. The dynamic cluster sizing affords a potential balance between exploration and exploitation and reduces the sensitivity to the cluster size in the niching methods. Taking advantages of Gaussian and Cauchy distributions, we generate the offspring at the niche level through alternatively using these two distributions. Such utilization can also potentially offer a balance between exploration and exploitation. Further, solution accuracy is enhanced through a new local search scheme probabilistically conducted around seeds of niches with probabilities determined self-adaptively according to fitness values of these seeds. Extensive experiments conducted on 20 benchmark multimodal problems confirm that both algorithms can achieve competitive performance compared with several state-of-the-art multimodal algorithms, which is supported by nonparametric tests. Especially, the proposed algorithms are very promising for complex problems with many local optima.

  • Item type:Article
    ID code:64792
    Dates:
    Date
    Event
    15 February 2016
    Published
    21 January 2016
    Accepted
    Notes:© 2016 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:19 Jul 2018 14:29
    Last modified:11 Apr 2024 01:31
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/64792
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