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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaolong Liu Lingli Huang Xianying Chang |
| Copyright Year | 2015 |
| Description | Author affiliation: Sch. of Bus. Adm., South China Univ. of Technol., Guangzhou, China (Xiaolong Liu; Lingli Huang; Xianying Chang) |
| Abstract | In view of the defect that the migration operator randomness is too strong to reduce the bacteria overall fitness, but not conducive to the overall optimization when bacteria foraging algorithm is in the optimization process. Then the pheromone of ant colony algorithm is introduced into the bacteria foraging algorithm. Through the migration of maximum pheromone and smaller pheromone, this paper improves the convergence precision, the global convergence ability of the original algorithm and establishes the hybrid bacteria foraging optimization algorithm. Meanwhile, the Cauchy variation is introduced in reproduction operation in order to enhance the global searching ability of algorithm. Then the paper adopts high dimensional complex standard functions to test these three kinds of bionic algorithms. The results indicate that the new algorithm significantly improves the search speed, partly avoids the local convergence problem and is more suitable for solving optimization problems of complex high dimensional engineering. |
| Starting Page | 1 |
| Ending Page | 7 |
| File Size | 354533 |
| Page Count | 7 |
| File Format | |
| e-ISBN | 9781479983285 |
| DOI | 10.1109/ICSSSM.2015.7170252 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-06-22 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Bacteria foraging algorithm Microorganisms Negative feedback Sociology Cauchy variation Pheromone Statistics Optimization Convergence |
| Content Type | Text |
| Resource Type | Article |
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