Evolutionary Optimization in Dynamic Environments
Published on 6. December 2012
XIV, 208 pages
978-1-4615-0911-0 (ISBN)
Description
Evolutionary Algorithms (EAs) have grown into a mature field of research in optimization, and have proven to be effective and robust problem solvers for a broad range of static real-world optimization problems. Yet, since they are based on the principles of natural evolution, and since natural evolution is a dynamic process in a changing environment, EAs are also well suited to dynamic optimization problems. Evolutionary Optimization in Dynamic Environments is the first comprehensive work on the application of EAs to dynamic optimization problems. It provides an extensive survey on research in the area and shows how EAs can be successfully used to
- continuously and efficiently adapt a solution to a changing environment,
- find a good trade-off between solution quality and adaptation cost,
- find robust solutions whose quality is insensitive to changes in the environment,
- find flexible solutions which are not only good but that can be easily adapted when necessary.
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Jürgen Branke
Evolutionary Optimization in Dynamic Environments
Book
10/2012
Springer
€213.99
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Content
1. Brief Introduction to Evolutionary Algorithms.- 1. From Biology to Software.- 2. Basic Evolutionary Algorithm.- 3. Further Aspects.- 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 1.- II Considering Adaptation Cost.- 7. Adaptation cost vs. Solution quality.- III Robustness and Flexibility - Precaution against Changes.- 8. Searching for Robust Solutions.- 9. From Robustness to Flexibility.- 10. Summary and Outlook.- References.
