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Disburdening the species conservation evolutionary algorithm of arguing with radii

Published: 07 July 2007 Publication History

Abstract

The present paper investigates the hybridization of two well-known multimodal optimization methods, i.e. species conservation and multinational algorithms. The topological species conservation algorithm embraces the vision of the existence of subpopulations around seeds (the best local individuals) and the preservation of these dominating individuals from one generation to another, but detects multimodality by means of the hill-valley mechanism employed by multinational algorithms. The aim is to inherit the strengths of both parent techniques and at the same time overcome their flaws. The species conservation algorithm efficiently keeps track of several good search space regions at once, but is difficult to parametrize without prior problem knowledge. Conversely, the multinational algorithms use many functionevaluations to establish subpopulations, but do not depend onprovided radius parameter values. Experiments with all threealgorithms are made on a wide range of test problems in order toinvestigate their advantages and shortcomings.

References

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  • (2024)Fundamental Tradeoffs Between Exploration and Exploitation Search MechanismsInto a Deeper Understanding of Evolutionary Computing: Exploration, Exploitation, and Parameter Control10.1007/978-3-031-74013-8_2(101-199)Online publication date: 12-Nov-2024
  • (2021)Solving Nonlinear Equations Systems with a Two-Phase Root-Finder Based on Niching Differential EvolutionBio-Inspired Computing: Theories and Applications10.1007/978-981-16-1354-8_17(251-268)Online publication date: 1-Apr-2021
  • (2019)Whale swarm algorithm with the mechanism of identifying and escaping from extreme points for multimodal function optimizationNeural Computing and Applications10.1007/s00521-018-3949-4Online publication date: 5-Jan-2019
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    cover image ACM Conferences
    GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
    July 2007
    2313 pages
    ISBN:9781595936974
    DOI:10.1145/1276958
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 07 July 2007

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    Author Tags

    1. detect-multimodal mechanism
    2. hybridization
    3. multimodal evolutionary algorithms
    4. species conservation

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    GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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    View all
    • (2024)Fundamental Tradeoffs Between Exploration and Exploitation Search MechanismsInto a Deeper Understanding of Evolutionary Computing: Exploration, Exploitation, and Parameter Control10.1007/978-3-031-74013-8_2(101-199)Online publication date: 12-Nov-2024
    • (2021)Solving Nonlinear Equations Systems with a Two-Phase Root-Finder Based on Niching Differential EvolutionBio-Inspired Computing: Theories and Applications10.1007/978-981-16-1354-8_17(251-268)Online publication date: 1-Apr-2021
    • (2019)Whale swarm algorithm with the mechanism of identifying and escaping from extreme points for multimodal function optimizationNeural Computing and Applications10.1007/s00521-018-3949-4Online publication date: 5-Jan-2019
    • (2017)Multimodal optimization by covariance matrix self-adaptation evolution strategy with repelling subpopulationsEvolutionary Computation10.1162/evco_a_0018225:3(439-471)Online publication date: 1-Sep-2017
    • (2017)Adaptive Multimodal Continuous Ant Colony OptimizationIEEE Transactions on Evolutionary Computation10.1109/TEVC.2016.259106421:2(191-205)Online publication date: 1-Apr-2017
    • (2017)Multimodal Estimation of Distribution AlgorithmsIEEE Transactions on Cybernetics10.1109/TCYB.2016.252300047:3(636-650)Online publication date: Mar-2017
    • (2017)Attraction basin sphere estimation approach for niching CMA-ESSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-015-1865-421:5(1327-1345)Online publication date: 1-Mar-2017
    • (2017)Evolutionary Multimodal OptimizationOptimization Methods and Applications10.1007/978-3-319-68640-0_8(137-181)Online publication date: 7-Dec-2017
    • (2015)History-Based Topological Speciation for Multimodal OptimizationIEEE Transactions on Evolutionary Computation10.1109/TEVC.2014.230667719:1(136-150)Online publication date: Feb-2015
    • (2015)An evolutionary algorithm based on decomposition for multimodal optimization problems2015 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2015.7257011(1091-1097)Online publication date: May-2015
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