Evolution strategies for robust optimization

Leiden Repository

Evolution strategies for robust optimization

Title: Evolution strategies for robust optimization
Author: Kruisselbrink, Johannes Willem
Publisher: Leiden Institute of Advanced Computer Science (LIACS), Faculty of Science, Leiden university
Issue Date: 2012-05-10
Keywords: Evolution Strategies
Evolutionary Algorithms
Input Uncertainty
Noisy Objective Functions
Robust Optimization
Abstract: Real-world (black-box) optimization problems often involve various types of uncertainties and noise emerging in different parts of the optimization problem. When this is not accounted for, optimization may fail or may yield solutions that are optimal in the classical strict notion of optimality, but fail in practice. Robust optimization is the practice of optimization that actively accounts for uncertainties and/or noise. Evolutionary Algorithms form a class of optimization algorithms that use the principle of evolution to find good solutions to optimization problems. Because uncertainty and noise are indispensable parts of nature, this class of optimization algorithms seems to be a logical choice for robust optimization scenarios. This thesis provides a clear definition of the term robust optimization and a comparison and practical guidelines on how Evolution Strategies, a subclass of Evolutionary Algorithms for real-parameter optimization problems, should be adapted for such scenarios.
Description: Promotor: T.H.W. Bäck, Co-promotor: M.T.M. Emmerich
With summary in Dutch
Faculty: Faculteit der Wiskunde en Natuurwetenschappen
Citation: Kruisselbrink, J.W., 2012, Doctoral thesis, Leiden University
ISBN: 9789461912503
Handle: http://hdl.handle.net/1887/18931

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application/pdf Cover 460.6Kb View/Open
application/pdf Title page_Contents 117.0Kb View/Open
application/pdf Chapter 1 Introduction 254.2Kb View/Open
application/pdf Part I From optimization to robust optimization 73.80Kb View/Open
application/pdf Chapter 2 396.9Kb View/Open
application/pdf Chapter 3 369.6Kb View/Open
application/pdf Part II Evoluti ... es for robust optimization 73.82Kb View/Open
application/pdf Chapter 4 549.3Kb View/Open
application/pdf Chapter 5 1.277Mb View/Open
application/pdf Chapter 6 982.2Kb View/Open
application/pdf Chapter 7 3.148Mb View/Open
application/pdf Chapter 8 539.7Kb View/Open
application/pdf Conclusion 184.0Kb View/Open
application/pdf Chapter 9 Bibliography 234.6Kb View/Open
application/pdf Appendices 10.32Mb View/Open
application/pdf Summary in Dutch 117.6Kb View/Open
application/pdf Curriculum Vitae 95.78Kb View/Open
application/pdf Propositions 117.7Kb View/Open

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