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Table of Contents
No Free Lunch Theorems: Limitations and Perspectives of Metaheuristics
Convergence Rates of Evolutionary Algorithms and Parallel Evolutionary Algorithms
Rugged and Elementary Landscapes
Single-Funnel and Multi-funnel Landscapes and Subthreshold Seeking Behavior
Black-Box Complexity for Bounding the Performance of Randomized Search Heuristics
Designing an Optimal Search Algorithm with Respect to Prior Information
The Bayesian Search Game
Principled Design of Continuous Stochastic Search: From Theory to Practice
Parsimony Pressure Made Easy: Solving the Problem of Bloat in GP
Experimental Analysis of Optimization Algorithms: Tuning and Beyond
Formal Search Algorithms + Problem Characterizations = Executable Search Strategies.
Convergence Rates of Evolutionary Algorithms and Parallel Evolutionary Algorithms
Rugged and Elementary Landscapes
Single-Funnel and Multi-funnel Landscapes and Subthreshold Seeking Behavior
Black-Box Complexity for Bounding the Performance of Randomized Search Heuristics
Designing an Optimal Search Algorithm with Respect to Prior Information
The Bayesian Search Game
Principled Design of Continuous Stochastic Search: From Theory to Practice
Parsimony Pressure Made Easy: Solving the Problem of Bloat in GP
Experimental Analysis of Optimization Algorithms: Tuning and Beyond
Formal Search Algorithms + Problem Characterizations = Executable Search Strategies.