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Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks

In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series...

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Detalles Bibliográficos
Autores principales: Lin, Na, Chen, Hanning, Jing, Shikai, Liu, Fang, Liang, Xiaodan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372419/
https://www.ncbi.nlm.nih.gov/pubmed/28386187
http://dx.doi.org/10.1016/j.sjbs.2017.01.033
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author Lin, Na
Chen, Hanning
Jing, Shikai
Liu, Fang
Liang, Xiaodan
author_facet Lin, Na
Chen, Hanning
Jing, Shikai
Liu, Fang
Liang, Xiaodan
author_sort Lin, Na
collection PubMed
description In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series of multi-swarm particle swarm optimizers called PS(2)Os, which extend the single population particle swarm optimization (PSO) algorithm to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations. According to different symbiotic interrelationships, four versions of PS(2)O are initiated to mimic mutualism, commensalism, predation, and competition mechanism, respectively. In the experiments, with five benchmark problems, the proposed algorithms are proved to have considerable potential for solving complex optimization problems. The coevolutionary dynamics of symbiotic species in each PS(2)O version are also studied respectively to demonstrate the heterogeneity of different symbiotic interrelationships that effect on the algorithm’s performance. Then PS(2)O is used for solving the radio frequency identification (RFID) network planning (RNP) problem with a mixture of discrete and continuous variables. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.
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spelling pubmed-53724192017-04-06 Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks Lin, Na Chen, Hanning Jing, Shikai Liu, Fang Liang, Xiaodan Saudi J Biol Sci Original Article In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series of multi-swarm particle swarm optimizers called PS(2)Os, which extend the single population particle swarm optimization (PSO) algorithm to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations. According to different symbiotic interrelationships, four versions of PS(2)O are initiated to mimic mutualism, commensalism, predation, and competition mechanism, respectively. In the experiments, with five benchmark problems, the proposed algorithms are proved to have considerable potential for solving complex optimization problems. The coevolutionary dynamics of symbiotic species in each PS(2)O version are also studied respectively to demonstrate the heterogeneity of different symbiotic interrelationships that effect on the algorithm’s performance. Then PS(2)O is used for solving the radio frequency identification (RFID) network planning (RNP) problem with a mixture of discrete and continuous variables. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness. Elsevier 2017-03 2017-01-25 /pmc/articles/PMC5372419/ /pubmed/28386187 http://dx.doi.org/10.1016/j.sjbs.2017.01.033 Text en © 2017 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Lin, Na
Chen, Hanning
Jing, Shikai
Liu, Fang
Liang, Xiaodan
Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks
title Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks
title_full Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks
title_fullStr Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks
title_full_unstemmed Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks
title_short Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks
title_sort biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in rfid networks
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372419/
https://www.ncbi.nlm.nih.gov/pubmed/28386187
http://dx.doi.org/10.1016/j.sjbs.2017.01.033
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