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Theory of Evolutionary Computation Recent Developments in Discrete Optimization

This edited book reports on recent developments in the theory of evolutionary computation, or more generally the domain of randomized search heuristics. It starts with two chapters on mathematical methods that are often used in the analysis of randomized search heuristics, followed by three chapters...

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Bibliographic Details
Other Authors: Doerr, Benjamin (Editor), Neumann, Frank (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2020, 2020
Edition:1st ed. 2020
Series:Natural Computing Series
Subjects:
Operations Research
Optimization
Computer Science
Artificial Intelligence
Theory Of Computation
Mathematical Optimization
Operations Research And Decision Theory
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Probabilistic Tools for the Analysis of Randomized Optimization Heuristics
  • Drift Analysis
  • Complexity Theory for Discrete Black-Box Optimization Heuristics
  • Parameterized Complexity Analysis of Randomized Search Heuristics
  • Analysing Stochastic Search Heuristics Operating on a Fixed Budget
  • Theory of Parameter Control for Discrete Black-Box Optimization: Provable Performance Gains Through Dynamic Parameter Choices
  • Analysis of Evolutionary Algorithms in Dynamic and Stochastic Environments
  • The Benefits of Population Diversity in Evolutionary Algorithms: A Survey of Rigorous Runtime Analyses
  • Theory of Estimation-of-Distribution Algorithms
  • Theoretical Foundations of Immune-Inspired Randomized Search Heuristics for Optimization
  • Computational Complexity Analysis of Genetic Programming

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