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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| Published in | Memetic computing Vol. 6; no. 1; pp. 31 - 47 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.03.2014
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1865-9284 1865-9292 |
| DOI | 10.1007/s12293-013-0128-0 |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Jadon, Shimpi Singh Sharma, Harish Clerc, Maurice Bansal, Jagdish Chand |
| Author_xml | – sequence: 1 givenname: Jagdish Chand surname: Bansal fullname: Bansal, Jagdish Chand email: jcbansal@gmail.com organization: ABV-Indian Institute of Information Technology and Management, South Asian, University – sequence: 2 givenname: Harish surname: Sharma fullname: Sharma, Harish organization: South Asian, University – sequence: 3 givenname: Shimpi Singh surname: Jadon fullname: Jadon, Shimpi Singh organization: ABV-Indian Institute of Information Technology and Management – sequence: 4 givenname: Maurice surname: Clerc fullname: Clerc, Maurice organization: Independent Consultant in Optimization |
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| Keywords | Spider monkey optimization Swarm intelligence based algorithm Optimization Fission–fusion social system |
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| SubjectTerms | Applications of Mathematics Artificial Intelligence Bioinformatics Complex Systems Control Engineering Mathematical and Computational Engineering Mechatronics Regular Research Paper Robotics |
| Title | Spider Monkey Optimization algorithm for numerical optimization |
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