Fitness Based Position Update in Spider Monkey Optimization Algorithm

被引:16
作者
Kumar, Sandeep [1 ]
Kumari, Rajani [1 ]
Sharma, Vivek Kumar [1 ]
机构
[1] Jagannath Univ, Jaipur 303901, Rajasthan, India
来源
PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND SOFTWARE ENGINEERING (SCSE'15) | 2015年 / 62卷
关键词
Spider Monkey Optimization Algorithm; Swarm intelligence; Engineering optimization problems; Nature Inspired Algorithms; fission-fusion social structure; GLOBAL OPTIMIZATION;
D O I
10.1016/j.procs.2015.08.504
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Spider Monkey Optimization (SMO) technique is most recent member in the family of swarm optimization algorithms.SMO algorithm fall in class of Nature Inspired Algorithm (NIA). SMO algorithm is good in exploration and exploitation of local search space and it is well balanced algorithm most of the times. This paper presents a new strategy to update position of solution during local leader phase using fitness of individuals. The proposed algorithm is named as Fitness based Position Update in SMO (FPSMO) algorithm as it updates position of individuals based on their fitness. The anticipated strategy enhances the rate of convergence. The planned FPSMO approach tested over nineteen benchmark functions and for one real world problem so as to establish superiority of it over basic SMO algorithm. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:442 / 449
页数:8
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