Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. Later, binary gravitational search algorith...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
2015
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| Online Access: | http://umpir.ump.edu.my/id/eprint/11826/ http://umpir.ump.edu.my/id/eprint/11826/1/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf http://umpir.ump.edu.my/id/eprint/11826/7/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf |
| _version_ | 1848819084978814976 |
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| author | Ismail, Ibrahim Zuwairie, Ibrahim Zulkifli, Md. Yusof |
| author_facet | Ismail, Ibrahim Zuwairie, Ibrahim Zulkifli, Md. Yusof |
| author_sort | Ismail, Ibrahim |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. Later, binary gravitational search algorithm (BGSA) is designed to solve discrete optimization problems. In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. The algorithm operates based on a simplified mechanism of transition between two states. The algorithm able to produce feasible solution in solving traveling salesman problem (TSP), one of the most intensively studied discrete combinatorial optimization problems. To evaluate the performances of the proposed algorithm and the BGSA, several experiments using six sets of selected benchmarks instances of traveling salesman problem (TSP) are conducted. The experimental results showed the newly introduced approach consistently outperformed the BGSA in all TSP benchmark instances used. |
| first_indexed | 2025-11-15T01:47:56Z |
| format | Conference or Workshop Item |
| id | ump-11826 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T01:47:56Z |
| publishDate | 2015 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-118262018-02-08T00:59:59Z http://umpir.ump.edu.my/id/eprint/11826/ Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem Ismail, Ibrahim Zuwairie, Ibrahim Zulkifli, Md. Yusof TK Electrical engineering. Electronics Nuclear engineering Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. Later, binary gravitational search algorithm (BGSA) is designed to solve discrete optimization problems. In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. The algorithm operates based on a simplified mechanism of transition between two states. The algorithm able to produce feasible solution in solving traveling salesman problem (TSP), one of the most intensively studied discrete combinatorial optimization problems. To evaluate the performances of the proposed algorithm and the BGSA, several experiments using six sets of selected benchmarks instances of traveling salesman problem (TSP) are conducted. The experimental results showed the newly introduced approach consistently outperformed the BGSA in all TSP benchmark instances used. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11826/1/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11826/7/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf Ismail, Ibrahim and Zuwairie, Ibrahim and Zulkifli, Md. Yusof (2015) Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem. In: 4th International Conference on Software Engineering and Computer Systems , 19-21 August 2015 , Kuantan, Pahang, Malaysia. pp. 142-147.. (Published) http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7333099 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Ismail, Ibrahim Zuwairie, Ibrahim Zulkifli, Md. Yusof Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem |
| title | Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem |
| title_full | Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem |
| title_fullStr | Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem |
| title_full_unstemmed | Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem |
| title_short | Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem |
| title_sort | rule-based multi-state gravitational search algorithm for discrete optimization problem |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/11826/ http://umpir.ump.edu.my/id/eprint/11826/ http://umpir.ump.edu.my/id/eprint/11826/1/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf http://umpir.ump.edu.my/id/eprint/11826/7/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf |