Comparison of optimization methods based on GSA

Year 2017, Special Issue (2017), 47 - 50, 24.09.2017

Nihan Kazak Nesibe Yalçın Ali Erdem Çerçevik

Abstract

In recent years, many heuristic evolutionary optimization algorithms have been developed. Gravitational search algorithm (GSA) is one of these algorithms. It is inspired by Newton’s law of universal gravitation. In this paper, we compare two modified algorithms based on GSA. One of the algorithms is called Member-Satellite algorithm. Members are randomly positioned in the search space and a certain amount of satellites are assigned around the members in the predetermined region. Members and their satellites are used to find a near optimal solution all together. The second one is MSS-GSA. When interconnected objects are used, it is possible to obtain a solution closer to the optimum point. For this reason mass spring system is integrated into the GSA. Three benchmark functions are used to compare performance. Experimental results show that the highest performance is obtained with Member-Satellite algorithm.

Keywords

gravitational search algorithm, heuristic algorithm, optimization, swarm intelligence

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