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

Selecciones Matemáticas

Haroldo F. Campos Velho¹  Reynier Hernández Torres¹  Eduardo F. P. da Luz² 

[1] Associated Laboratory for Computing and Applied Mathematics (LAC), National Institute for Space Research (INPE), Sao José dos Campos, Sao Paulo, Brazil;Centro Nacional de Monitoramento e Alertas de Desastres Naturais (Cemaden), Sao José dos Campos, Sao Paulo, Brazil;

关键词: stochastic algorithm;    metaheuristic;    opposition-based learning;    reflection-based learning;    multi-particle collision algorithm;   

DOI  :  10.17268/sel.mat.2019.02.03

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown