Self-organizing Migrating Algorithm with Non-binary Perturbation
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The self-organizing migrating algorithm (SOMA) is a popular population base metaheuristic. One of its key mechanisms is a perturbation of the individual movement with a binary-valued perturbation (PRT) vector. The goal of perturbation is to improve the diversity of the population and exploration of the search space. In this paper, we study a variant of the SOMA algorithm with non-binary PRT vector. We investigate the effect of introducing a third possible value, a negative (repulsive) element, into the PRT vector. The aim is to slow the population convergence and prolong the exploration phase. The inspiration is taken from previous successful implementations of repulsive mechanics in another swarm-based method: the Particle Swarm Optimization.
KeywordsSelf-organizing migrating algorithm SOMA Repulsivity Perturbation
This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme Project no. LO1303 (MSMT-7778/2014), further by the European Regional Development Fund under the Project CEBIA-Tech no. CZ.1.05/2.1.00/03.0089 and by Internal Grant Agency of Tomas Bata University under the Projects no. IGA/CebiaTech/2019/002. This work is also based upon support by COST (European Cooperation in Science & Technology) under Action CA15140, Improving Applicability of Nature-Inspired Optimisation by Joining Theory and Practice (ImAppNIO), and Action IC1406, High-Performance Modelling, and Simulation for Big Data Applications (cHiPSet). The work was further supported by resources of A.I.Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).
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