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Using predators and preys in evolution strategies

Published: 25 June 2005 Publication History

Abstract

This poster presents an evolution strategy for single- and multi-objective optimization. The model uses the predator-prey approach from ecology to scale between both cases. Furthermore the main issue of adaptation working for single- and multi-objective problem-instances equally is discussed. Particular, the well proved self-adaptation mechanism for the mutation strengths in the single-objective case is adopted for the multi-objective one. This self-adaptation process is supported by a new strategy of competition between predators and preys. Six test functions are used to demonstrate the practicability of the model.

Cited By

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  • (2018)Coevolutionary Multiobjective Evolutionary Algorithms: Survey of the State-of-the-ArtIEEE Transactions on Evolutionary Computation10.1109/TEVC.2017.276702322:6(851-865)Online publication date: Dec-2018
  • (2008)The Parallel Predator-Prey ModelProceedings of the 10th International Conference on Parallel Problem Solving from Nature --- PPSN X - Volume 519910.5555/2951659.2951731(681-690)Online publication date: 13-Sep-2008
  • (2008)Simulated evolution under multiple criteria conditions revisitedProceedings of the 2008 IEEE world conference on Computational intelligence: research frontiers10.5555/1788915.1788930(249-261)Online publication date: 1-Jun-2008
  • Show More Cited By

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    cover image ACM Conferences
    GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation
    June 2005
    2272 pages
    ISBN:1595930108
    DOI:10.1145/1068009
    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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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 25 June 2005

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    Author Tags

    1. evolution strategy
    2. multi criterion
    3. predator-prey

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    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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    Cited By

    View all
    • (2018)Coevolutionary Multiobjective Evolutionary Algorithms: Survey of the State-of-the-ArtIEEE Transactions on Evolutionary Computation10.1109/TEVC.2017.276702322:6(851-865)Online publication date: Dec-2018
    • (2008)The Parallel Predator-Prey ModelProceedings of the 10th International Conference on Parallel Problem Solving from Nature --- PPSN X - Volume 519910.5555/2951659.2951731(681-690)Online publication date: 13-Sep-2008
    • (2008)Simulated evolution under multiple criteria conditions revisitedProceedings of the 2008 IEEE world conference on Computational intelligence: research frontiers10.5555/1788915.1788930(249-261)Online publication date: 1-Jun-2008
    • (2008)Technology Transfer: Academia to IndustryEvolutionary Computation in Practice10.1007/978-3-540-75771-9_12(263-281)Online publication date: 2008
    • (2008)Simulated Evolution under Multiple Criteria Conditions RevisitedComputational Intelligence: Research Frontiers10.1007/978-3-540-68860-0_12(249-261)Online publication date: 2008
    • (2007)Designing multi-objective variation operators using a predator-prey approachProceedings of the 4th international conference on Evolutionary multi-criterion optimization10.5555/1762545.1762553(21-35)Online publication date: 5-Mar-2007
    • (2006)Inside a predator-prey model for multi-objective optimizationProceedings of the 8th annual conference on Genetic and evolutionary computation10.1145/1143997.1144121(707-714)Online publication date: 8-Jul-2006

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