Spider Monkey Optimization algorithm for numerical optimization

Swarm intelligence is one of the most promising area for the researchers in the field of numerical optimization. Researchers have developed many algorithms by simulating the swarming behavior of various creatures like ants, honey bees, fish, birds and the findings are very motivating. In this paper,...

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Bibliographic Details
Published inMemetic computing Vol. 6; no. 1; pp. 31 - 47
Main Authors Bansal, Jagdish Chand, Sharma, Harish, Jadon, Shimpi Singh, Clerc, Maurice
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2014
Subjects
Applications of Mathematics
Artificial Intelligence
Bioinformatics
Complex Systems
Control
Engineering
Mathematical and Computational Engineering
Mechatronics
Regular Research Paper
Robotics
Spider monkey optimization
Swarm intelligence based algorithm
Optimization
Fission–fusion social system
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ISSN1865-9284
1865-9292
DOI10.1007/s12293-013-0128-0

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Summary:Swarm intelligence is one of the most promising area for the researchers in the field of numerical optimization. Researchers have developed many algorithms by simulating the swarming behavior of various creatures like ants, honey bees, fish, birds and the findings are very motivating. In this paper, a new approach for numerical optimization is proposed by modeling the foraging behavior of spider monkeys. Spider monkeys have been categorized as fission–fusion social structure based animals. The animals which follow fission–fusion social systems, split themselves from large to smaller groups and vice-versa based on the scarcity or availability of food. The proposed swarm intelligence approach is named as Spider Monkey Optimization (SMO) algorithm and can broadly be classified as an algorithm inspired by intelligent foraging behavior of fission–fusion social structure based animals.
ISSN:1865-9284
1865-9292
DOI:10.1007/s12293-013-0128-0