Evolutionary Computation with Biogeography-based Optimization

Table of contents

1. Cover
2. Title
3. Copyright
4. 1 The Science of Biogeography
   1. 1.1. Introduction
   2. 1.2. Island biogeography
   3. 1.3. Influence factors for biogeography
5. 2 Biogeography and Biological Optimization
   1. 2.1. A mathematical model of biogeography
   2. 2.2. Biogeography as an optimization process
   3. 2.3. Biological optimization
   4. 2.4. Conclusion
6. 3 A Basic BBO Algorithm
   1. 3.1. BBO definitions and algorithm
   2. 3.2. Differences between BBO and other optimization algorithms
   3. 3.3. Simulations
   4. 3.4. Conclusion
7. 4 BBO Extensions
   1. 4.1. Migration curves
   2. 4.2. Blended migration
   3. 4.3. Other approaches to BBO
   4. 4.4. Applications
   5. 4.5. Conclusion
8. 5 BBO as a Markov Process
   1. 5.1. Markov definitions and notations
   2. 5.2. Markov model of BBO
   3. 5.3. BBO convergence
   4. 5.4. Markov models of BBO extensions
   5. 5.5. Conclusions
9. 6 Dynamic System Models of BBO
   1. 6.1. Basic notation
   2. 6.2. Dynamic system models of BBO
   3. 6.3. Applications to benchmark problems
   4. 6.4. Conclusions
10. 7 Statistical Mechanics Approximations of BBO
    1. 7.1. Preliminary foundation
    2. 7.2. Statistical mechanics model of BBO
    3. 7.3. Further discussion
    4. 7.4. Conclusions
11. 8 BBO for Combinatorial Optimization
    1. 8.1. Traveling salesman problem
    2. 8.2. BBO for the TSP
    3. 8.3. Graph coloring
    4. 8.4. Knapsack problem
    5. 8.5. Conclusion
12. 9 Constrained BBO
    1. 9.1. Constrained optimization
    2. 9.2. Constraint-handling methods
    3. 9.3. BBO for constrained optimization
    4. 9.4. Conclusion
13. 10 BBO in Noisy Environments
    1. 10.1. Noisy fitness functions
    2. 10.2. Influence of noise on BBO
    3. 10.3. BBO with re-sampling
    4. 10.4. The Kalman BBO
    5. 10.5. Experimental results
    6. 10.6. Conclusion
14. 11 Multi-objective BBO
    1. 11.1. Multi-objective optimization problems
    2. 11.2. Multi-objective BBO
    3. 11.3. Real-world applications
    4. 11.4. Conclusion
15. 12 Hybrid BBO Algorithms
    1. 12.1. Opposition-based BBO
    2. 12.2. BBO with local search
    3. 12.3. BBO with other EAs
    4. 12.4. Conclusion
16. APPENDICES
    1. Appendix A: Unconstrained Benchmark Functions
    2. Appendix B: Constrained Benchmark Functions
    3. Appendix C: Multi-objective Benchmark Functions
17. Bibliography
18. Index
19. End User License Agreement