An Algorithm for Global Optimization Inspired by Collective Animal Behavior
A metaheuristic algorithm for global optimization called the collective animal behavior (CAB) is introduced. Animal groups, such as schools of fish, flocks of birds, swarms of locusts, and herds of wildebeest, exhibit a variety of behaviors including swarming about a food source, milling around a ce...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2012/638275 |
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| _version_ | 1832564106798825472 |
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| author | Erik Cuevas Mauricio González Daniel Zaldivar Marco Pérez-Cisneros Guillermo García |
| author_facet | Erik Cuevas Mauricio González Daniel Zaldivar Marco Pérez-Cisneros Guillermo García |
| author_sort | Erik Cuevas |
| collection | DOAJ |
| description | A metaheuristic algorithm for global optimization called the collective animal behavior (CAB) is introduced. Animal groups, such as schools of fish, flocks of birds, swarms of locusts, and herds of wildebeest, exhibit a variety of behaviors including swarming about a food source, milling around a central locations, or migrating over large distances in aligned groups. These collective behaviors are often advantageous to groups, allowing them to increase their harvesting efficiency, to follow better migration routes, to improve their aerodynamic, and to avoid predation. In the proposed algorithm, the searcher agents emulate a group of animals which interact with each other based on the biological laws of collective motion. The proposed method has been compared to other well-known optimization algorithms. The results show good performance of the proposed method when searching for a global optimum of several benchmark functions. |
| format | Article |
| id | doaj-art-1c30fb6353c74c998c965e8bb69ec747 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-1c30fb6353c74c998c965e8bb69ec7472025-02-03T01:11:44ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2012-01-01201210.1155/2012/638275638275An Algorithm for Global Optimization Inspired by Collective Animal BehaviorErik Cuevas0Mauricio González1Daniel Zaldivar2Marco Pérez-Cisneros3Guillermo García4CUCEI Departamento de Electrónica, Universidad de Guadalajara, Avenida Revolución 1500, 44100 Guadalajara, JAL, MexicoCUCEI Departamento de Electrónica, Universidad de Guadalajara, Avenida Revolución 1500, 44100 Guadalajara, JAL, MexicoCUCEI Departamento de Electrónica, Universidad de Guadalajara, Avenida Revolución 1500, 44100 Guadalajara, JAL, MexicoCUCEI Departamento de Electrónica, Universidad de Guadalajara, Avenida Revolución 1500, 44100 Guadalajara, JAL, MexicoCUCEI Departamento de Electrónica, Universidad de Guadalajara, Avenida Revolución 1500, 44100 Guadalajara, JAL, MexicoA metaheuristic algorithm for global optimization called the collective animal behavior (CAB) is introduced. Animal groups, such as schools of fish, flocks of birds, swarms of locusts, and herds of wildebeest, exhibit a variety of behaviors including swarming about a food source, milling around a central locations, or migrating over large distances in aligned groups. These collective behaviors are often advantageous to groups, allowing them to increase their harvesting efficiency, to follow better migration routes, to improve their aerodynamic, and to avoid predation. In the proposed algorithm, the searcher agents emulate a group of animals which interact with each other based on the biological laws of collective motion. The proposed method has been compared to other well-known optimization algorithms. The results show good performance of the proposed method when searching for a global optimum of several benchmark functions.http://dx.doi.org/10.1155/2012/638275 |
| spellingShingle | Erik Cuevas Mauricio González Daniel Zaldivar Marco Pérez-Cisneros Guillermo García An Algorithm for Global Optimization Inspired by Collective Animal Behavior Discrete Dynamics in Nature and Society |
| title | An Algorithm for Global Optimization Inspired by Collective Animal Behavior |
| title_full | An Algorithm for Global Optimization Inspired by Collective Animal Behavior |
| title_fullStr | An Algorithm for Global Optimization Inspired by Collective Animal Behavior |
| title_full_unstemmed | An Algorithm for Global Optimization Inspired by Collective Animal Behavior |
| title_short | An Algorithm for Global Optimization Inspired by Collective Animal Behavior |
| title_sort | algorithm for global optimization inspired by collective animal behavior |
| url | http://dx.doi.org/10.1155/2012/638275 |
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