A Modified Salp Swarm Algorithm Based on the Perturbation Weight for Global Optimization Problems
Metaheuristic algorithms are often applied to global function optimization problems. To overcome the poor real-time performance and low precision of the basic salp swarm algorithm, this paper introduces a novel hybrid algorithm inspired by the perturbation weight mechanism. The proposed perturbation...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/6371085 |
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| _version_ | 1832550093260062720 |
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| author | Yuqi Fan Junpeng Shao Guitao Sun Xuan Shao |
| author_facet | Yuqi Fan Junpeng Shao Guitao Sun Xuan Shao |
| author_sort | Yuqi Fan |
| collection | DOAJ |
| description | Metaheuristic algorithms are often applied to global function optimization problems. To overcome the poor real-time performance and low precision of the basic salp swarm algorithm, this paper introduces a novel hybrid algorithm inspired by the perturbation weight mechanism. The proposed perturbation weight salp swarm algorithm has the advantages of a broad search scope and a strong balance between exploration and exploitation and retains a relatively low computational complexity when dealing with numerous large-scale problems. A new coefficient factor is introduced to the basic salp swarm algorithm, and new update strategies for the leader position and the followers are introduced in the search phase. The new leader position updating strategy has a specific bounded scope and strong search performance, thus accelerating the iteration process. The new follower updating strategy maintains the diversity of feasible solutions while reducing the computational load. This paper describes the application of the proposed algorithm to low-dimension and variable-dimension functions. This paper also presents iteration curves, box-plot charts, and search-path graphics to verify the accuracy of the proposed algorithm. The experimental results demonstrate that the perturbation weight salp swarm algorithm offers a better search speed and search balance than the basic salp swarm algorithm in different environments. |
| format | Article |
| id | doaj-art-af86bb8ae648401daf1cab25e4fa38fb |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-af86bb8ae648401daf1cab25e4fa38fb2025-02-03T06:07:41ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/63710856371085A Modified Salp Swarm Algorithm Based on the Perturbation Weight for Global Optimization ProblemsYuqi Fan0Junpeng Shao1Guitao Sun2Xuan Shao3Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, ChinaKey Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, ChinaKey Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, ChinaKey Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, ChinaMetaheuristic algorithms are often applied to global function optimization problems. To overcome the poor real-time performance and low precision of the basic salp swarm algorithm, this paper introduces a novel hybrid algorithm inspired by the perturbation weight mechanism. The proposed perturbation weight salp swarm algorithm has the advantages of a broad search scope and a strong balance between exploration and exploitation and retains a relatively low computational complexity when dealing with numerous large-scale problems. A new coefficient factor is introduced to the basic salp swarm algorithm, and new update strategies for the leader position and the followers are introduced in the search phase. The new leader position updating strategy has a specific bounded scope and strong search performance, thus accelerating the iteration process. The new follower updating strategy maintains the diversity of feasible solutions while reducing the computational load. This paper describes the application of the proposed algorithm to low-dimension and variable-dimension functions. This paper also presents iteration curves, box-plot charts, and search-path graphics to verify the accuracy of the proposed algorithm. The experimental results demonstrate that the perturbation weight salp swarm algorithm offers a better search speed and search balance than the basic salp swarm algorithm in different environments.http://dx.doi.org/10.1155/2020/6371085 |
| spellingShingle | Yuqi Fan Junpeng Shao Guitao Sun Xuan Shao A Modified Salp Swarm Algorithm Based on the Perturbation Weight for Global Optimization Problems Complexity |
| title | A Modified Salp Swarm Algorithm Based on the Perturbation Weight for Global Optimization Problems |
| title_full | A Modified Salp Swarm Algorithm Based on the Perturbation Weight for Global Optimization Problems |
| title_fullStr | A Modified Salp Swarm Algorithm Based on the Perturbation Weight for Global Optimization Problems |
| title_full_unstemmed | A Modified Salp Swarm Algorithm Based on the Perturbation Weight for Global Optimization Problems |
| title_short | A Modified Salp Swarm Algorithm Based on the Perturbation Weight for Global Optimization Problems |
| title_sort | modified salp swarm algorithm based on the perturbation weight for global optimization problems |
| url | http://dx.doi.org/10.1155/2020/6371085 |
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