Evolutionary Optimization in Dynamic Environments

Evolutionary Optimization in Dynamic Environments by Jürgen Branke.

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 evolu...

Full description

Saved in:
Bibliographic Details
Main Author: Branke, Jürgen (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York, NY : Springer US : Imprint: Springer, 2002.
Edition:1st ed. 2002.
Series:Genetic Algorithms and Evolutionary Computation, 3
Springer eBook Collection.
Subjects:
Artificial intelligence.
Computers.
Calculus of variations.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 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.

Similar Items