Enhancement of the Multi-Particle Collision Algorithm by mechanisms derived from the Opposition-Based Optimization

Authors

  • Reynier Hernández Torres Associated Laboratory for Computing and Applied Mathematics (LAC), National Institute for Space Research (INPE), Sao José dos Campos, Sao Paulo, Brazil http://orcid.org/0000-0003-1554-5145
  • Haroldo F. Campos Velho Associated Laboratory for Computing and Applied Mathematics (LAC), National Institute for Space Research (INPE), Sao José dos Campos, Sao Paulo, Brazil http://orcid.org/0000-0003-4968-5330
  • Eduardo F. P. da Luz Centro Nacional de Monitoramento e Alertas de Desastres Naturais (Cemaden), Sao José dos Campos, Sao Paulo, Brazil http://orcid.org/0000-0003-2081-1831

DOI:

https://doi.org/10.17268/sel.mat.2019.02.03

Keywords:

Stochastic algorithm, Metaheuristic, Opposition-Based Learning, Reflection-Based Learning, Multi-Particle Collision Algorithm

Abstract

New versions of the metaheuristic Multi-Particle Collision Algorithm (MPCA) are presented. In order to provide more effective candidate solutions for an optimization problem, the concept of opposition and reflection is introduced to improve the capacity to find a solution in the search space. Four different strategies to compute the reflected and opposite points are implemented. The performance of all implementations is evaluated over thirty objective functions with different complexities, using serial and parallel versions of the algorithms.

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Published

2019-12-24

How to Cite

Hernández Torres, R., Campos Velho, H. F., & P. da Luz, E. F. (2019). Enhancement of the Multi-Particle Collision Algorithm by mechanisms derived from the Opposition-Based Optimization. Selecciones Matemáticas, 6(02), 156-177. https://doi.org/10.17268/sel.mat.2019.02.03

Issue

Vol. 6 No. 02 (2019): August - December

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Articles

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