A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems
The intention of this hybridization is to further enhance the exploratory and exploitative search capabilities involving simple concepts. The proposed algorithm adopts the combined discrete and continuous probability distribution scheme of ant colony optimization (ACO) to specifically assist genetic...
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| Format: | Article |
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Taylor & Francis
2019
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| _version_ | 1796961801055764480 |
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| author | Tam, Jun Hui Ong, Zhi Chao Ismail, Zubaidah Ang, Bee Chin Khoo, Shin Yee |
| author_facet | Tam, Jun Hui Ong, Zhi Chao Ismail, Zubaidah Ang, Bee Chin Khoo, Shin Yee |
| author_sort | Tam, Jun Hui |
| collection | UM |
| description | The intention of this hybridization is to further enhance the exploratory and exploitative search capabilities involving simple concepts. The proposed algorithm adopts the combined discrete and continuous probability distribution scheme of ant colony optimization (ACO) to specifically assist genetic algorithm in the aspect of exploratory search. Besides, distinctive crossover and mutation operators are introduced, in which, two types of mutation operators, namely, standard mutation and refined mutation are suggested. In early iterations, standard mutation is utilized collaboratively with the concept of unrepeated tours of ACO to evade local entrapment, while refined mutation is used in later iterations to supplement the exploitative search, which is mainly controlled by particle swarm optimization. The proposed method has been validated in solving test functions and well-known engineering design problems. It exhibits a great global search capability even in the presence of non-linearity, multimodality and constraints, involving a large number of dimensions as well as large search areas. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. |
| first_indexed | 2024-03-06T05:59:33Z |
| format | Article |
| id | um.eprints-23328 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:59:33Z |
| publishDate | 2019 |
| publisher | Taylor & Francis |
| record_format | dspace |
| spelling | um.eprints-233282020-01-06T03:58:58Z http://eprints.um.edu.my/23328/ A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems Tam, Jun Hui Ong, Zhi Chao Ismail, Zubaidah Ang, Bee Chin Khoo, Shin Yee TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TP Chemical technology The intention of this hybridization is to further enhance the exploratory and exploitative search capabilities involving simple concepts. The proposed algorithm adopts the combined discrete and continuous probability distribution scheme of ant colony optimization (ACO) to specifically assist genetic algorithm in the aspect of exploratory search. Besides, distinctive crossover and mutation operators are introduced, in which, two types of mutation operators, namely, standard mutation and refined mutation are suggested. In early iterations, standard mutation is utilized collaboratively with the concept of unrepeated tours of ACO to evade local entrapment, while refined mutation is used in later iterations to supplement the exploitative search, which is mainly controlled by particle swarm optimization. The proposed method has been validated in solving test functions and well-known engineering design problems. It exhibits a great global search capability even in the presence of non-linearity, multimodality and constraints, involving a large number of dimensions as well as large search areas. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. Taylor & Francis 2019 Article PeerReviewed Tam, Jun Hui and Ong, Zhi Chao and Ismail, Zubaidah and Ang, Bee Chin and Khoo, Shin Yee (2019) A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems. International Journal of Computer Mathematics, 96 (5). pp. 883-919. ISSN 0020-7160, DOI https://doi.org/10.1080/00207160.2018.1463438 <https://doi.org/10.1080/00207160.2018.1463438>. https://doi.org/10.1080/00207160.2018.1463438 doi:10.1080/00207160.2018.1463438 |
| spellingShingle | TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TP Chemical technology Tam, Jun Hui Ong, Zhi Chao Ismail, Zubaidah Ang, Bee Chin Khoo, Shin Yee A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems |
| title | A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems |
| title_full | A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems |
| title_fullStr | A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems |
| title_full_unstemmed | A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems |
| title_short | A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems |
| title_sort | new hybrid ga aco pso algorithm for solving various engineering design problems |
| topic | TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TP Chemical technology |
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