Preface. 1. Brief Introduction to Evolutionary Algorithms. Part I: Enabling Continuous Adaptation. 2. Optimization in Dynamic Environments. 3. Survey: State of the Art. 4. From Memory to Self-Organization. 5. Empirical Evaluation. 6. Summary of Part I. Part II: Considering Adaptation Cost. 7. Adaptation Cost vs. Solution Quality. Part III: Robustness and Flexibility - Precaution against Changes. 8. Searching for Robust Solutions. 9. From Robustness to Flexibility. 10. Summary and Outlook. References. Index.
['Jürgen Branke']
Evolutionary Optimization in Dynamic Environments