Global-best harmony search

被引:584
作者
Omran, Mahamed G. H. [1 ]
Mahdavi, Mehrdad [2 ]
机构
[1] Gulf Univ Sci & Technol, Dept Comp Sci, Kuwait, Kuwait
[2] Sharif Univ Technol, Dept Comp Engn, Tehran, Iran
关键词
harmony search; meta-heuristics; evolutionary algorithms; optimization;
D O I
10.1016/j.amc.2007.09.004
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Harmony search (HS) is a new meta-heuristic optimization method imitating the music improvisation process where musicians improvise their instruments' pitches searching for a perfect state of harmony. A new variant of HS, called global-best harmony search (GHS), is proposed in this paper where concepts from swarm intelligence are borrowed to enhance the performance of HS. The performance of the GHS is investigated and compared with HS and a recently developed variation of HS. The experiments conducted show that the GHS generally outperformed the other approaches when applied to ten benchmark problems. The effect of noise on the performance of the three HS variants is investigated and a scalability study is conducted. The effect of the GHS parameters is analyzed. Finally, the three HS variants are compared on several Integer Programming test problems. The results show that the three approaches seem to be an efficient alternative for solving Integer Programming problems. (C) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码:643 / 656
页数:14
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