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A Selective Biogeography-Based Optimizer Considering Resource Allocation for Large-Scale Global Optimization
- Source :
- Computational Intelligence and Neuroscience, Computational Intelligence and Neuroscience, 2019, pp.1-18. ⟨10.1155/2019/1240162⟩, Computational Intelligence and Neuroscience, Hindawi Publishing Corporation, 2019, pp.1-18. ⟨10.1155/2019/1240162⟩, Computational Intelligence and Neuroscience, Vol 2019 (2019)
- Publication Year :
- 2019
- Publisher :
- HAL CCSD, 2019.
-
Abstract
- Biogeography-based optimization (BBO), a recent proposed metaheuristic algorithm, has been successfully applied to many optimization problems due to its simplicity and efficiency. However, BBO is sensitive to the curse of dimensionality; its performance degrades rapidly as the dimensionality of the search space increases. In this paper, a selective migration operator is proposed to scale up the performance of BBO and we name it selective BBO (SBBO). The differential migration operator is selected heuristically to explore the global area as far as possible whist the normal distributed migration operator is chosen to exploit the local area. By the means of heuristic selection, an appropriate migration operator can be used to search the global optimum efficiently. Moreover, the strategy of cooperative coevolution (CC) is adopted to solve large-scale global optimization problems (LSOPs). To deal with subgroup imbalance contribution to the whole solution in the context of CC, a more efficient computing resource allocation is proposed. Extensive experiments are conducted on the CEC 2010 benchmark suite for large-scale global optimization, and the results show the effectiveness and efficiency of SBBO compared with BBO variants and other representative algorithms for LSOPs. Also, the results confirm that the proposed computing resource allocation is vital to the large-scale optimization within the limited computation budget.
- Subjects :
- Mathematical optimization
Optimization problem
Cooperative coevolution
General Computer Science
Article Subject
Computer science
General Mathematics
Normal Distribution
02 engineering and technology
lcsh:Computer applications to medicine. Medical informatics
Computing Methodologies
lcsh:RC321-571
Resource Allocation
0202 electrical engineering, electronic engineering, information engineering
Heuristics
Computer Simulation
lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry
Global optimization
Metaheuristic
Problem Solving
ComputingMilieux_MISCELLANEOUS
Heuristic
General Neuroscience
020207 software engineering
General Medicine
Benchmark (computing)
lcsh:R858-859.7
Resource allocation
020201 artificial intelligence & image processing
[INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Algorithms
Curse of dimensionality
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 16875265 and 16875273
- Database :
- OpenAIRE
- Journal :
- Computational Intelligence and Neuroscience, Computational Intelligence and Neuroscience, 2019, pp.1-18. ⟨10.1155/2019/1240162⟩, Computational Intelligence and Neuroscience, Hindawi Publishing Corporation, 2019, pp.1-18. ⟨10.1155/2019/1240162⟩, Computational Intelligence and Neuroscience, Vol 2019 (2019)
- Accession number :
- edsair.doi.dedup.....c0ad7a4d0472a03ea167ca26d2af5adc