Verfügbarkeit: A brief introduction to continuous evolutionary optimization

A brief introduction to continuous evolutionary optimization:

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1. Verfasser:	Kramer, Oliver (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Cham [u.a.] Springer 2014
Schriftenreihe:	SpringerBriefs in applied sciences and technology
Schlagworte:	Ingenieurwissenschaften Künstliche Intelligenz Artificial intelligence Engineering
Online-Zugang:	BTU01 FHA01 FHI01 FHN01 FHR01 FKE01 FRO01 FWS01 FWS02 UBY01 Volltext Inhaltsverzeichnis Abstract
Beschreibung:	1 Online-Ressource
ISBN:	9783319034225
DOI:	10.1007/978-3-319-03422-5

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adam_text	A BRIEF INTRODUCTION TO CONTINUOUS EVOLUTIONARY OPTIMIZATION / KRAMER, OLIVER : 2014 TABLE OF CONTENTS / INHALTSVERZEICHNIS PART I FOUNDATIONS PART II ADVANCED OPTIMIZATION PART III LEARNING PART IV APPENDIX DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT. A BRIEF INTRODUCTION TO CONTINUOUS EVOLUTIONARY OPTIMIZATION / KRAMER, OLIVER : 2014 ABSTRACT / INHALTSTEXT PRACTICAL OPTIMIZATION PROBLEMS ARE OFTEN HARD TO SOLVE, IN PARTICULAR WHEN THEY ARE BLACK BOXES AND NO FURTHER INFORMATION ABOUT THE PROBLEM IS AVAILABLE EXCEPT VIA FUNCTION EVALUATIONS. THIS WORK INTRODUCES A COLLECTION OF HEURISTICS AND ALGORITHMS FOR BLACK BOX OPTIMIZATION WITH EVOLUTIONARY ALGORITHMS IN CONTINUOUS SOLUTION SPACES. THE BOOK GIVES AN INTRODUCTION TO EVOLUTION STRATEGIES AND PARAMETER CONTROL. HEURISTIC EXTENSIONS ARE PRESENTED THAT ALLOW OPTIMIZATION IN CONSTRAINED, MULTIMODAL, AND MULTI-OBJECTIVE SOLUTION SPACES. AN ADAPTIVE PENALTY FUNCTION IS INTRODUCED FOR CONSTRAINED OPTIMIZATION. META-MODELS REDUCE THE NUMBER OF FITNESS AND CONSTRAINT FUNCTION CALLS IN EXPENSIVE OPTIMIZATION PROBLEMS. THE HYBRIDIZATION OF EVOLUTION STRATEGIES WITH LOCAL SEARCH ALLOWS FAST OPTIMIZATION IN SOLUTION SPACES WITH MANY LOCAL OPTIMA. A SELECTION OPERATOR BASED ON REFERENCE LINES IN OBJECTIVE SPACE IS INTRODUCED TO OPTIMIZE MULTIPLE CONFLICTIVE OBJECTIVES. EVOLUTIONARY SEARCH IS EMPLOYED FOR LEARNING KERNEL PARAMETERS OF THE NADARAYA-WATSON ESTIMATOR, AND A SWARM-BASED ITERATIVE APPROACH IS PRESENTED FOR OPTIMIZING LATENT POINTS IN DIMENSIONALITY REDUCTION PROBLEMS. EXPERIMENTS ON TYPICAL BENCHMARK PROBLEMS AS WELL AS NUMEROUS FIGURES AND DIAGRAMS ILLUSTRATE THE BEHAVIOR OF THE INTRODUCED CONCEPTS AND METHODS DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
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spellingShingle	Kramer, Oliver A brief introduction to continuous evolutionary optimization Ingenieurwissenschaften Künstliche Intelligenz Artificial intelligence Engineering
title	A brief introduction to continuous evolutionary optimization
title_auth	A brief introduction to continuous evolutionary optimization
title_exact_search	A brief introduction to continuous evolutionary optimization
title_full	A brief introduction to continuous evolutionary optimization Oliver Kramer
title_fullStr	A brief introduction to continuous evolutionary optimization Oliver Kramer
title_full_unstemmed	A brief introduction to continuous evolutionary optimization Oliver Kramer
title_short	A brief introduction to continuous evolutionary optimization
title_sort	a brief introduction to continuous evolutionary optimization
topic	Ingenieurwissenschaften Künstliche Intelligenz Artificial intelligence Engineering
topic_facet	Ingenieurwissenschaften Künstliche Intelligenz Artificial intelligence Engineering
url	https://doi.org/10.1007/978-3-319-03422-5 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027014972&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027014972&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA
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