Population topologies for particle swarm optimization and differential evolution
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 diver...
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sg-ntu-dr.10356-1385542020-05-08T04:27:33Z Population topologies for particle swarm optimization and differential evolution Lynn, Nandar Mostafa Z. Ali Suganthan, Ponnuthurai Nagaratnam School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Particle Swarm Optimization Differential Evolution 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. 2020-05-08T04:27:33Z 2020-05-08T04:27:33Z 2017 Journal Article 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 2210-6502 https://hdl.handle.net/10356/138554 10.1016/j.swevo.2017.11.002 2-s2.0-85034605668 39 24 35 en Swarm and Evolutionary Computation © 2017 Elsevier B.V. All rights reserved. |
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Engineering::Electrical and electronic engineering Particle Swarm Optimization Differential Evolution Lynn, Nandar Mostafa Z. Ali Suganthan, Ponnuthurai Nagaratnam Population topologies for particle swarm optimization and differential evolution |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Lynn, Nandar Mostafa Z. Ali Suganthan, Ponnuthurai Nagaratnam |
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Article |
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Lynn, Nandar Mostafa Z. Ali Suganthan, Ponnuthurai Nagaratnam |
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Lynn, Nandar |
title |
Population topologies for particle swarm optimization and differential evolution |
title_short |
Population topologies for particle swarm optimization and differential evolution |
title_full |
Population topologies for particle swarm optimization and differential evolution |
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Population topologies for particle swarm optimization and differential evolution |
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Population topologies for particle swarm optimization and differential evolution |
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population topologies for particle swarm optimization and differential evolution |
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2020 |
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https://hdl.handle.net/10356/138554 |
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1681058631538180096 |