Hybrid Biogeography-Based Optimization for Integer Programming
Biogeography-based optimization (BBO) is a relatively new bioinspired heuristic for global optimization based on the mathematical models of biogeography. By investigating the applicability and performance of BBO for integer programming, we find that the original BBO algorithm does not perform well o...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/672983 |
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| _version_ | 1849407039893143552 |
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| author | Zhi-Cheng Wang Xiao-Bei Wu |
| author_facet | Zhi-Cheng Wang Xiao-Bei Wu |
| author_sort | Zhi-Cheng Wang |
| collection | DOAJ |
| description | Biogeography-based optimization (BBO) is a relatively new bioinspired heuristic for global optimization based on the mathematical models of biogeography. By investigating the applicability and performance of BBO for integer programming, we find that the original BBO algorithm does not perform well on a set of benchmark integer programming problems. Thus we modify the mutation operator and/or the neighborhood structure of the algorithm, resulting in three new BBO-based methods, named BlendBBO, BBO_DE, and LBBO_LDE, respectively. Computational experiments show that these methods are competitive approaches to solve integer programming problems, and the LBBO_LDE shows the best performance on the benchmark problems. |
| format | Article |
| id | doaj-art-4642eef4467a40ba9bfd9130b76a2ef5 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-4642eef4467a40ba9bfd9130b76a2ef52025-08-20T03:36:12ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/672983672983Hybrid Biogeography-Based Optimization for Integer ProgrammingZhi-Cheng Wang0Xiao-Bei Wu1College of Electronics and Information Engineering, Tongji University, Shanghai 201804, ChinaCollege of Electronics and Information Engineering, Tongji University, Shanghai 201804, ChinaBiogeography-based optimization (BBO) is a relatively new bioinspired heuristic for global optimization based on the mathematical models of biogeography. By investigating the applicability and performance of BBO for integer programming, we find that the original BBO algorithm does not perform well on a set of benchmark integer programming problems. Thus we modify the mutation operator and/or the neighborhood structure of the algorithm, resulting in three new BBO-based methods, named BlendBBO, BBO_DE, and LBBO_LDE, respectively. Computational experiments show that these methods are competitive approaches to solve integer programming problems, and the LBBO_LDE shows the best performance on the benchmark problems.http://dx.doi.org/10.1155/2014/672983 |
| spellingShingle | Zhi-Cheng Wang Xiao-Bei Wu Hybrid Biogeography-Based Optimization for Integer Programming The Scientific World Journal |
| title | Hybrid Biogeography-Based Optimization for Integer Programming |
| title_full | Hybrid Biogeography-Based Optimization for Integer Programming |
| title_fullStr | Hybrid Biogeography-Based Optimization for Integer Programming |
| title_full_unstemmed | Hybrid Biogeography-Based Optimization for Integer Programming |
| title_short | Hybrid Biogeography-Based Optimization for Integer Programming |
| title_sort | hybrid biogeography based optimization for integer programming |
| url | http://dx.doi.org/10.1155/2014/672983 |
| work_keys_str_mv | AT zhichengwang hybridbiogeographybasedoptimizationforintegerprogramming AT xiaobeiwu hybridbiogeographybasedoptimizationforintegerprogramming |