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Chaotic krill herd optimization algorithm

被引：75
|
作者：
Saremi, Shahrzad [1 ]
Mirjalili, Seyed Mohammad [2 ]
Mirjalili, Seyedali [3 ]
机构：
[1] Univ Queensland, Fac Engn Architecture & Informat Technol, Brisbane, Qld 4072, Australia
[2] Shahid Beheshti Univ, Fac Elect & Comp Engn, GC, Tehran, Iran
[3] Griffith Univ, Sch Commun Informat & Technol, Brisbane, Qld, Australia
来源：
7TH INTERNATIONAL CONFERENCE INTERDISCIPLINARITY IN ENGINEERING (INTER-ENG 2013) | 2014年 / 12卷
关键词：
chaos theory; optimization; chaotic maps; KH; heuristics; PARTICLE SWARM OPTIMIZATION;
D O I：
10.1016/j.protcy.2013.12.473
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The Krill Herd (KH) optimization algorithm is one of the most recent heuristic optimization techniques. This algorithm mimics the lifecycle of krill in oceans. Despite high performance of KH, stagnation in local optima and slow convergence speed are two probable problems in solving challenging optimization problems. This work enhances the performance of the KH algorithm by the chaos theory. To be exact, three one-dimensional chaotic maps (Circle, Sine, and Tent) are integrated into KH. The results prove that the proposed chaotic KH algorithms are able to show superior results compared to KH in terms of local optima avoidance and convergence speed. (C) 2013 The Authors. Published by Elsevier Ltd.
引用
收藏
页码：180 / 185
页数：6
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