GEM: A novel evolutionary optimization method with improved neighborhood search

被引:27
作者
Ahrari, A. [1 ]
Shariat-Panahi, M. [1 ]
Atai, A. A. [1 ]
机构
[1] Univ Tehran, Dept Mech Engn, Tehran, Iran
关键词
Stochastic optimization methods; Evolutionary algorithms; Multimodal functions; Agent's territory; Guided random search; Optimal search direction; Multiple global minima; SIMULATED ANNEALING ALGORITHM; COLONY ABC ALGORITHM; GENETIC ALGORITHM; DESIGN;
D O I
10.1016/j.amc.2009.01.009
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A new optimization technique called Grenade Explosion Method (GEM) is introduced and its underlying ideas, including the concept of Optimal Search Direction (OSD), are elaborated. The applicability and efficiency of the technique is demonstrated using standard benchmark functions. Comparison of the results with those of other, widely-used, evolutionary algorithms shows that the proposed algorithm outperforms its rivals both in the success rate and rate of convergence. The method is also shown to be capable of finding most, or even all, optima of functions having multiple global optima. Moreover, it is shown that the performance of GEM is invariant against shifting and scaling of the search space and objective function. (c) 2009 Elsevier Inc. All rights reserved.
引用
收藏
页码:376 / 386
页数:11
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