【Wiley 最优化】 Evolutionary Computation with Biogeography-based Optimiz (2017)

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Evolutionary Computation with Biogeography-based Optimization

Haiping Ma, Dan Simon



Evolutionary computation algorithms are employed to minimize functions with large number of variables. Biogeography-based optimization (BBO) is an optimization algorithm that is based on the science of biogeography, which researches the migration patterns of species. These migration paradigms provide the main logic behind BBO. Due to the cross-disciplinary nature of the optimization problems, there is a need to develop multiple approaches to tackle them and to study the theoretical reasoning behind their performance. This manuscript intends to explain the mathematical model of BBO algorithm and its variants created to cope with continuous domain problems (with and without constraints) and combinatorial problems.

Due to the cross-disciplinary nature of the optimization problems, there is a need to develop multiple approaches to tackle them and to study the theoretical reasoning behind their performance. This manuscript intends to explain the mathematical model of BBO algorithm and its variants created to cope with continuous domain problems (with and without constraints) and combinatorial problems.

Table of Contents

1. The science of biogeography

2. Biogeography and biological optimization

3. A basic BBO algorithm

4. BBO extensions

5. BBO as Markov processes (Markov models, and convergence)

6. Dynamic system models of BBO

7. Statistical mechanics approximations of BBO

8. BBO for combinatorial problems

9. Constrained BBO

10. BBO in Noisy Environments

11. Multi-objective BBO

12. Hybrid BBO algorithms (BBO and DE, BBO and PSO, BBO

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关键词：Evolutionary Computation Geography Evolution Comput problems provide science number nature

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Evolutionary Computation with Biogeography-based Optimization

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Haiping Ma, Dan Simon-Evolutionary Computation with Biogeography-based Optimization