Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/138554
Title: Population topologies for particle swarm optimization and differential evolution
Authors: Lynn, Nandar
Mostafa Z. Ali
Suganthan, Ponnuthurai Nagaratnam
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2017
Source: Lynn, N., Mostafa Z. Ali, & Suganthan, P. N. (2018). Population topologies for particle swarm optimization and differential evolution. Swarm and Evolutionary Computation, 39, 24-35. doi:10.1016/j.swevo.2017.11.002
Journal: Swarm and Evolutionary Computation
Abstract: Over the last few decades, many population-based swarm and evolutionary algorithms were introduced in the literature. It is well known that population topology or sociometry plays an important role in improving the performance of population-based optimization algorithms by enhancing population diversity when solving multiobjective and multimodal problems. Many population structures and population topologies were developed for particle swarm optimization and differential evolutionary algorithms. Therefore, a comprehensive review of population topologies developed for PSO and DE is carried out in this paper. We anticipate that this survey will inspire researchers to integrate the population topologies into other nature inspired algorithms and to develop novel population topologies for improving the performances of population-based optimization algorithms for solving single objective optimization, multiobjective optimization and other classes of optimization problems.
URI: https://hdl.handle.net/10356/138554
ISSN: 2210-6502
DOI: 10.1016/j.swevo.2017.11.002
Rights: © 2017 Elsevier B.V. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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