Theory and Principled Methods for the Design of Metaheuristics

1. No Free Lunch Theorems: Limitations and Perspectives of Metaheuristics
Christian Igel

2. Convergence Rates of Evolutionary Algorithms and Parallel Evolutionary Algorithms
Fabien Teytaud, Olivier Teytaud

3. Rugged and Elementary Landscapes
Konstantin Klemm, Peter F. Stadler

4. Single-Funnel and Multi-funnel Landscapes and Subthreshold-Seeking Behavior
Darrell Whitley, Jonathan Rowe

5. Black-Box Complexity for Bounding the Performance of Randomized Search Heuristics
Thomas Jansen

6. Designing an Optimal Search Algorithm with Respect to Prior Information
Olivier Teytaud, Emmanuel Vazquez

7. The Bayesian Search Game
Marc Toussaint

8. Principled Design of Continuous Stochastic Search: From Theory to Practice
Nikolaus Hansen, Anne Auger

9. Parsimony Pressure Made Easy: Solving the Problem of Bloat in GP
Riccardo Poli, Nicholas Freitag McPhee

10. Experimental Analysis of Optimization Algorithms: Tuning and Beyond
Thomas Bartz-Beielstein, Mike Preuss

11. Formal Search Algorithms + Problem Characterisations = Executable Search Strategies
Patrick D. Surry, Nicholas J. Radcliffe

Keywords: Computer Science, Theory of Computation, Computational Intelligence, Artificial Intelligence (incl. Robotics), Optimization, Operation Research/Decision Theory