Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization

The new era knowledge of optimization algorithm is massively boosted recently. Among several optimization models, multi-swarm approach has been proposed most recently for balancing the exploration and exploitation capability through the Particle Swarm Optimization (PSO) algorithm. The proposed multi...

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Main Authors: Salih, Sinan Q., Alsewari, Abdulrahman A., Yaseen, Zeher M.
Format: Conference or Workshop Item
Language:English
Published: Association for Computing Machinery 2019
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Online Access:http://umpir.ump.edu.my/id/eprint/22272/1/Pressure%20Vessel%20Design%20Simulation1.pdf
http://umpir.ump.edu.my/id/eprint/22272/
https://dx.doi.org/10.1145/3316615.3316643
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Institution: Universiti Malaysia Pahang
Language: English
id my.ump.umpir.22272
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spelling my.ump.umpir.222722020-01-13T01:25:33Z http://umpir.ump.edu.my/id/eprint/22272/ Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization Salih, Sinan Q. Alsewari, Abdulrahman A. Yaseen, Zeher M. Q Science (General) T Technology (General) TA Engineering (General). Civil engineering (General) The new era knowledge of optimization algorithm is massively boosted recently. Among several optimization models, multi-swarm approach has been proposed most recently for balancing the exploration and exploitation capability through the Particle Swarm Optimization (PSO) algorithm. The proposed multi-swarm model which is called Meeting Room Approach (MRA), is tested and evaluated based on solving normal and large-scale problems. In the current research, the feasibility of the proposed Multi-Swarm Particle Swarm Optimization (MPSO) is adopted to simulate mechanical engineering problem namely pressure vessel design (PVD). The results indicated the potential of the proposed MPSO model on simulating the PVD problem with optimum solution over the standalone PSO. Further, the current study results authenticated against other famous meta-heuristics. Overall, MPSO reported an excellent optimization solution with fast convergence learning process. Association for Computing Machinery 2019 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/22272/1/Pressure%20Vessel%20Design%20Simulation1.pdf Salih, Sinan Q. and Alsewari, Abdulrahman A. and Yaseen, Zeher M. (2019) Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization. In: ICSCA '19: Proceedings of the 2019 8th International Conference on Software and Computer Applications, 19-22 February 2019 , Penang, Malaysia. pp. 120-124.. ISBN 978-1-4503-6573-4 https://dx.doi.org/10.1145/3316615.3316643
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic Q Science (General)
T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle Q Science (General)
T Technology (General)
TA Engineering (General). Civil engineering (General)
Salih, Sinan Q.
Alsewari, Abdulrahman A.
Yaseen, Zeher M.
Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization
description The new era knowledge of optimization algorithm is massively boosted recently. Among several optimization models, multi-swarm approach has been proposed most recently for balancing the exploration and exploitation capability through the Particle Swarm Optimization (PSO) algorithm. The proposed multi-swarm model which is called Meeting Room Approach (MRA), is tested and evaluated based on solving normal and large-scale problems. In the current research, the feasibility of the proposed Multi-Swarm Particle Swarm Optimization (MPSO) is adopted to simulate mechanical engineering problem namely pressure vessel design (PVD). The results indicated the potential of the proposed MPSO model on simulating the PVD problem with optimum solution over the standalone PSO. Further, the current study results authenticated against other famous meta-heuristics. Overall, MPSO reported an excellent optimization solution with fast convergence learning process.
format Conference or Workshop Item
author Salih, Sinan Q.
Alsewari, Abdulrahman A.
Yaseen, Zeher M.
author_facet Salih, Sinan Q.
Alsewari, Abdulrahman A.
Yaseen, Zeher M.
author_sort Salih, Sinan Q.
title Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization
title_short Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization
title_full Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization
title_fullStr Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization
title_full_unstemmed Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization
title_sort pressure vessel design simulation: implementing of multi-swarm particle swarm optimization
publisher Association for Computing Machinery
publishDate 2019
url http://umpir.ump.edu.my/id/eprint/22272/1/Pressure%20Vessel%20Design%20Simulation1.pdf
http://umpir.ump.edu.my/id/eprint/22272/
https://dx.doi.org/10.1145/3316615.3316643
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