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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. Evolutionary Computation with Biogeography-Based Optimization explains the mathematical model of BBO algorithm and its variants created to cope with continuous domain problems (with and without constraints) and combinatorial problems.
Chapter 1. The Science of Biogeography 1
Chapter 2. Biogeography and Biological Optimization 11
Chapter 3. A Basic BBO Algorithm 25
Chapter 4. BBO Extensions 45
Chapter 5. BBO as a Markov Process 61
Chapter 6. Dynamic System Models of BBO 103
Chapter 7. Statistical Mechanics Approximations of BBO 123
Chapter 8. BBO for Combinatorial Optimization 145
Chapter 9. Constrained BBO 169
Chapter 10. BBO in Noisy Environments 187
Chapter 11. Multi-objective BBO 203
Chapter 12. Hybrid BBO Algorithms 233
Appendices 259
Bibliography 309
Index 325
