Hybridizing gravitational search algorithm with real coded genetic algorithms for structural engineering design problem

作     者：Singh, Amarjeet Deep, Kusum 

作者机构：Indian Inst Technol Roorkee Dept Math Roorkee 247667 Uttarakhand India 

出 版 物：《OPSEARCH》 (运筹学；印度运筹学会志)

年 卷 期：2017年第54卷第3期

页      面：505-536页

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：Council for Scientific and Industrial Research (CSIR)  New Delhi  IndiaCouncil of Scientific & Industrial Research (CSIR) - India [09/143(0824)/2012-EMR-I] 

主　　题：Gravitational search algorithm Laplace crossover Power mutation Engineering optimization 

摘      要：The focus of this paper is gravitational search algorithm which is a relatively new heuristics algorithm for function optimization. In order to improve the efficiency and reliability it was hybridized with real coded genetic algorithm and extensively applied to solve benchmarks problems available in literature. In the present paper, these hybridized variants are used to solve three constrained engineering design problem. The obtained results are compared with an extensively available results in literature. It is proved that the performance of one of the hybridized version outperform the remaining hybridized version as well as original gravitational search algorithm, in term of quality of solution and computation effort.