An improved multi-state particle swarm optimization for discrete combinatorial optimization problems

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)

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Abstract

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.

Item Type:	Article
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Discrete combinatorial optimization problem; Multi-state; Particle swarm optimization
Subjects:	Q Science > QA Mathematics T Technology > T Technology (General)
Faculty/Division:	Institute of Postgraduate Studies College of Engineering Faculty of Manufacturing and Mechatronic Engineering Technology
Depositing User:	Mrs Norsaini Abdul Samat
Date Deposited:	28 Oct 2021 07:51
Last Modified:	28 Oct 2021 07:51
URI:	http://umpir.ump.edu.my/id/eprint/29595
Download Statistic:	View Download Statistics

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