A Multi-state Gravitational Search Algorithm for 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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Bibliographic Details
Published in:	2015 7th International Conference on Computational Intelligence, Communication Systems and Networks pp. 9 - 14
Main Authors:	Ibrahim, Ismail, Ibrahim, Zuwairie, Ahmad, Hamzah, Yusof, Zulkifli Md
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.06.2015
Subjects:	Algorithm design and analysis Approximation algorithms Benchmark testing Cities and towns discrete combinatorial optimization problem Force gravitational search algorithm Heuristic algorithms multi-state Optimization rule-based travelling salesman problem
Online Access:	Get full text
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Summary:	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 experimental results show the effectiveness of the newly introduced approach, regarding its ability to consistently outperform the binary-based algorithm in solving the discrete optimization problems.
DOI:	10.1109/CICSyN.2015.12