ACROA: Artificial Chemical Reaction Optimization Algorithm for global optimization

被引:299
作者
Alatas, Bilal [1 ]
机构
[1] Tunceli Univ, Dept Comp Engn, TR-62000 Tunceli, Turkey
关键词
Heuristic optimization; Computational method; Chemical reaction; Performance; PARTICLE SWARM OPTIMIZATION; GENETIC ALGORITHM; SEARCH; COLONY; SYSTEM;
D O I
10.1016/j.eswa.2011.04.126
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Heuristic based computational algorithms are densely being used in many different fields due to their advantages. When investigated carefully, chemical reactions possess efficient objects, states, process, and events that can be designed as a computational method en bloc. In this study, a novel computational method, which is more robust and have less parameters than that of used in the literature, is intended to be developed inspiring from types and occurring of chemical reactions. The proposed method is named as Artificial Chemical Reaction Optimization Algorithm, ACROA. Applications to multiple-sequence alignment, data mining, and benchmark functions have been performed so as to put forward the performance of developed computational method. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:13170 / 13180
页数:11
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