research-article

Island-cellular model differential evolution for large-scale global optimization

Authors:

Rodolfo A. Lopes,

Alan R. R. de FreitasAuthors Info & Claims

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Pages 1841 - 1848

https://doi.org/10.1145/3067695.3084208

Published: 15 July 2017 Publication History

Abstract

The Island-Cellular Model (ICM) is an important population distribution approach for Evolutionary Algorithms (EAs). This hybrid approach combines the Island Model (IM) and Cellular Model (CM) in a two-layer hierarchical model. Although the ICM has been shown to be an efficient way to implement EAs, there is still a lack of knowledge about its parameters and its performance for Large-Scale Global Optimization (LSGO) problems. However, the ICM approach is able to enrich the evolutionary search by keeping the population diversity in EAs. Thus, this paper proposes to implement the ICM approach for LSGO problems using the Differential Evolutionary (DE) algorithm. It also proposes an experimental study of the ICM parameters by investigating their impact on the EA. Experimental results on Large-Scale Global Optimization Benchmark Functions show that the ICM approach for the DE algorithm improves its performance. Furthermore, the results collected from different ICM approaches indicate that there is a trade-off between solution quality and convergence speed.

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Cited By

Seck-Tuoh-Mora JHernandez-Hurtado UMedina-Marín JHernández-Romero NLizárraga-Mendiola L(2024)Multi-Objective Majority–Minority Cellular Automata Algorithm for Global and Engineering Design OptimizationAlgorithms10.3390/a1710043317:10(433)Online publication date: 27-Sep-2024
https://doi.org/10.3390/a17100433
Araujo JBatista L(2023)A diversity-driven migration strategy for distributed evolutionary algorithmsSwarm and Evolutionary Computation10.1016/j.swevo.2023.10136182(101361)Online publication date: Oct-2023
https://doi.org/10.1016/j.swevo.2023.101361
He ZPeng HChen JDeng CWu Z(2020)A Spark-based differential evolution with grouping topology model for large-scale global optimizationCluster Computing10.1007/s10586-020-03124-zOnline publication date: 30-May-2020
https://doi.org/10.1007/s10586-020-03124-z

Index Terms

Island-cellular model differential evolution for large-scale global optimization
1. Theory of computation
  1. Design and analysis of algorithms
    1. Mathematical optimization
      1. Continuous optimization
        Bio-inspired optimization

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cover image ACM Conferences

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion

July 2017

1934 pages

ISBN:9781450349390

DOI:10.1145/3067695

Copyright © 2017 ACM.

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 the author(s) 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: 15 July 2017

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Universidade Federal de Ouro Preto

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GECCO '17

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GECCO '17: Genetic and Evolutionary Computation Conference

July 15 - 19, 2017

Berlin, Germany

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Cited By

Seck-Tuoh-Mora JHernandez-Hurtado UMedina-Marín JHernández-Romero NLizárraga-Mendiola L(2024)Multi-Objective Majority–Minority Cellular Automata Algorithm for Global and Engineering Design OptimizationAlgorithms10.3390/a1710043317:10(433)Online publication date: 27-Sep-2024
https://doi.org/10.3390/a17100433
Araujo JBatista L(2023)A diversity-driven migration strategy for distributed evolutionary algorithmsSwarm and Evolutionary Computation10.1016/j.swevo.2023.10136182(101361)Online publication date: Oct-2023
https://doi.org/10.1016/j.swevo.2023.101361
He ZPeng HChen JDeng CWu Z(2020)A Spark-based differential evolution with grouping topology model for large-scale global optimizationCluster Computing10.1007/s10586-020-03124-zOnline publication date: 30-May-2020
https://doi.org/10.1007/s10586-020-03124-z
Wang TLin CLiaw RTing C(2019)Empirical Analysis of Island Model on Large Scale Global Optimization2019 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2019.8790331(342-349)Online publication date: Jun-2019
https://doi.org/10.1109/CEC.2019.8790331

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