An improved multi-state particle swarm optimization for discrete combinatorial optimization problems
The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. Many improvements of the binary-based algorithms have been reported. In this paper, a variant of GSA called multi-state gravitational search algorithm (MSGSA)...
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| Format: | Article |
| Language: | English English |
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United Kingdom Simulation Society
2015
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| Online Access: | http://umpir.ump.edu.my/id/eprint/29595/ http://umpir.ump.edu.my/id/eprint/29595/1/An%20improved%20multi-state%20particle%20swarm%20optimization%20for%20discrete%20.pdf http://umpir.ump.edu.my/id/eprint/29595/2/An%20improved%20multi-state%20particle%20swarm%20optimization%20for%20discrete_FULL.pdf |
| _version_ | 1848823316223098880 |
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| author | Ismail, Ibrahim Zuwairie, Ibrahim Hamzah, Ahmad Zulkifli, Md. Yusof |
| author_facet | Ismail, Ibrahim Zuwairie, Ibrahim Hamzah, Ahmad Zulkifli, Md. Yusof |
| author_sort | Ismail, Ibrahim |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. Many improvements of the binary-based algorithms have been reported. In this paper, a variant of GSA called multi-state gravitational search algorithm (MSGSA) for discrete optimization problems is proposed. The MSGSA concept is based on a simplified mechanism of transition between two states. The performance of the MSGSA is empirically compared to the original BGSA based on six sets of selected benchmarks instances of traveling salesman problem (TSP). The results are statistically analyzed and show that the MSGSA has performed consistently in solving the discrete optimization problems. |
| first_indexed | 2025-11-15T02:55:12Z |
| format | Article |
| id | ump-29595 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T02:55:12Z |
| publishDate | 2015 |
| publisher | United Kingdom Simulation Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-295952021-10-28T07:51:08Z http://umpir.ump.edu.my/id/eprint/29595/ An improved multi-state particle swarm optimization for discrete combinatorial optimization problems Ismail, Ibrahim Zuwairie, Ibrahim Hamzah, Ahmad Zulkifli, Md. Yusof QA Mathematics T Technology (General) The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. Many improvements of the binary-based algorithms have been reported. In this paper, a variant of GSA called multi-state gravitational search algorithm (MSGSA) for discrete optimization problems is proposed. The MSGSA concept is based on a simplified mechanism of transition between two states. The performance of the MSGSA is empirically compared to the original BGSA based on six sets of selected benchmarks instances of traveling salesman problem (TSP). The results are statistically analyzed and show that the MSGSA has performed consistently in solving the discrete optimization problems. United Kingdom Simulation Society 2015-12 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/29595/1/An%20improved%20multi-state%20particle%20swarm%20optimization%20for%20discrete%20.pdf pdf en http://umpir.ump.edu.my/id/eprint/29595/2/An%20improved%20multi-state%20particle%20swarm%20optimization%20for%20discrete_FULL.pdf Ismail, Ibrahim and Zuwairie, Ibrahim and Hamzah, Ahmad and Zulkifli, Md. Yusof (2015) An improved multi-state particle swarm optimization for discrete combinatorial optimization problems. International Journal of Simulation: Systems, Science & Technology (IJSSST), 16 (6). 14.1-14.8. ISSN 1473-8031 (print); 1473-804x (online). (Published) https://doi.org/10.1109/CICSyN.2015.11 https://doi.org/10.1109/CICSyN.2015.11 |
| spellingShingle | QA Mathematics T Technology (General) Ismail, Ibrahim Zuwairie, Ibrahim Hamzah, Ahmad Zulkifli, Md. Yusof An improved multi-state particle swarm optimization for discrete combinatorial optimization problems |
| title | An improved multi-state particle swarm optimization for discrete combinatorial optimization problems |
| title_full | An improved multi-state particle swarm optimization for discrete combinatorial optimization problems |
| title_fullStr | An improved multi-state particle swarm optimization for discrete combinatorial optimization problems |
| title_full_unstemmed | An improved multi-state particle swarm optimization for discrete combinatorial optimization problems |
| title_short | An improved multi-state particle swarm optimization for discrete combinatorial optimization problems |
| title_sort | improved multi-state particle swarm optimization for discrete combinatorial optimization problems |
| topic | QA Mathematics T Technology (General) |
| url | http://umpir.ump.edu.my/id/eprint/29595/ http://umpir.ump.edu.my/id/eprint/29595/ http://umpir.ump.edu.my/id/eprint/29595/ http://umpir.ump.edu.my/id/eprint/29595/1/An%20improved%20multi-state%20particle%20swarm%20optimization%20for%20discrete%20.pdf http://umpir.ump.edu.my/id/eprint/29595/2/An%20improved%20multi-state%20particle%20swarm%20optimization%20for%20discrete_FULL.pdf |