An Improved Gravitational Search Algorithm Based on Neighbor Search

被引:0
|
作者
Wang, C. [1 ]
Gao, K. Z. [2 ]
Guo, J. [1 ]
机构
[1] Yangzhou Polytech Inst, Coll Elect & Informat Engn, Hanjiang, Peoples R China
[2] Liaocheng Univ, Sch Comp, Singapore, Singapore
关键词
meta-heuristic; gravitation search algorithm; random neighbor search; CENTRAL FORCE OPTIMIZATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The gravitational search algorithm (GSA) is a new meta-heuristic optimization method based on the law of gravity and mass interactions. An improved GSA (IGSA) is proposed in this paper where a neighbor search is employed to enhance the performance of GSA. The IGSA can obtain a better or best solution in a neighbor space through one or more times random neighbor search. Two different search methods are designed for the proposed improved gravitational search algorithm. In addition, the effect of the gravitational constant to the performance of the IGSA is discussed. Extensive computational experiments are carried out using well-known benchmark functions. Computational results and comparisons show the efficiency and effectiveness of the proposed IGSA.
引用
收藏
页码:681 / 685
页数:5
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