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The author takes a different approach in this textbook by focusing on the users' needs and answering three fundamental questions: First, he tells us which problems modern heuristics are expected to perform well on, and which should be left to traditional optimization methods. Second, he teaches us to systematically design the "right" modern heuristic for a particular problem by providing a coherent view on design elements and working principles. Third, he shows how we can make use of problem-specific knowledge for the design of efficient and effective modern heuristics that solve not only small toy problems but also perform well on large real-world problems.
This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use.
This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use.
This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use.
The author takes a different approach in this textbook by focusing on the users' needs and answering three fundamental questions: First, he tells us which problems modern heuristics are expected to perform well on, and which should be left to traditional optimization methods. Second, he teaches us to systematically design the "right" modern heuristic for a particular problem by providing a coherent view on design elements and working principles. Third, he shows how we can make use of problem-specific knowledge for the design of efficient and effective modern heuristics that solve not only small toy problems but also perform well on large real-world problems.
This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use.
This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use.
This book is written in an easy-to-read style and it is aimed at students and practitioners in computer science, operations research and information systems who want to understand modern heuristics and are interested in a guide to their systematic design and use.
Prof. Rothlauf completed his PhD thesis in 2001 at the University of Bayreuth, supervised by David E. Goldberg of the Illinois Genetic Algorithms Laboratory (IlliGAL). His particular areas of interest are optimization and heuristics, particulary in the areas of transportation, logistics and business information systems. He chaired the main international conference on evolutionary computing, ACM GECCO, in 2009, and has co-organized many related conferences and workshops; he has also acted as guest editor for related journal special issues; and he published the book "Representations for Genetic and Evolutionary Algorithms" in 2002, this was published in a second edition in 2006.
Many books describe the application of heuristic optimization methods to a wide variety of optimization problems. However, the process of developing an efficient optimization method for the specific problem at hand seems to be considered a "black art", the domain of optimization specialists. This book focuses on the practitioner and demonstrates how to apply heuristic optimization methods. It is the first book to offer a systematic theory of how to apply and adapt heuristic optimization methods. It breaks down the art of designing efficient optimization methods into engineering tasks, and examines how to build successful applications of heuristic optimization methods. In so doing the reader learns how to properly model the problem, choose the optimization method, adapt that method to the properties of the specific problem, and, finally, implement the method.
Chap. 1.- Introduction.- Part I.- Fundamentals.- Chap. 2.- Optimization Problems.- Chap. 3.- Optimization Methods.- Part II.- Modern Heuristics.- Chap. 4.- Design Elements.- Chap. 5.- Search Strategies.- Chap. 6.- Design Principles.- Part III Case Studies.- Chap. 7.- High Locality Representations for Automated Programming.- Chap. 8.-Biased Modern Heuristics for the OCST Problem.- Chap. 9.-Summary.- References.- Nomenclature.- Glossary.- Index
Erscheinungsjahr: | 2011 |
---|---|
Genre: | Informatik, Mathematik, Medizin, Naturwissenschaften, Technik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xi
267 S. |
ISBN-13: | 9783540729617 |
ISBN-10: | 3540729615 |
Sprache: | Englisch |
Herstellernummer: | 11818441 |
Einband: | Gebunden |
Autor: | Rothlauf, Franz |
Hersteller: |
Springer-Verlag GmbH
Springer Berlin Heidelberg |
Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
Maße: | 241 x 160 x 20 mm |
Von/Mit: | Franz Rothlauf |
Erscheinungsdatum: | 17.07.2011 |
Gewicht: | 0,588 kg |
Prof. Rothlauf completed his PhD thesis in 2001 at the University of Bayreuth, supervised by David E. Goldberg of the Illinois Genetic Algorithms Laboratory (IlliGAL). His particular areas of interest are optimization and heuristics, particulary in the areas of transportation, logistics and business information systems. He chaired the main international conference on evolutionary computing, ACM GECCO, in 2009, and has co-organized many related conferences and workshops; he has also acted as guest editor for related journal special issues; and he published the book "Representations for Genetic and Evolutionary Algorithms" in 2002, this was published in a second edition in 2006.
Many books describe the application of heuristic optimization methods to a wide variety of optimization problems. However, the process of developing an efficient optimization method for the specific problem at hand seems to be considered a "black art", the domain of optimization specialists. This book focuses on the practitioner and demonstrates how to apply heuristic optimization methods. It is the first book to offer a systematic theory of how to apply and adapt heuristic optimization methods. It breaks down the art of designing efficient optimization methods into engineering tasks, and examines how to build successful applications of heuristic optimization methods. In so doing the reader learns how to properly model the problem, choose the optimization method, adapt that method to the properties of the specific problem, and, finally, implement the method.
Chap. 1.- Introduction.- Part I.- Fundamentals.- Chap. 2.- Optimization Problems.- Chap. 3.- Optimization Methods.- Part II.- Modern Heuristics.- Chap. 4.- Design Elements.- Chap. 5.- Search Strategies.- Chap. 6.- Design Principles.- Part III Case Studies.- Chap. 7.- High Locality Representations for Automated Programming.- Chap. 8.-Biased Modern Heuristics for the OCST Problem.- Chap. 9.-Summary.- References.- Nomenclature.- Glossary.- Index
Erscheinungsjahr: | 2011 |
---|---|
Genre: | Informatik, Mathematik, Medizin, Naturwissenschaften, Technik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Buch |
Inhalt: |
xi
267 S. |
ISBN-13: | 9783540729617 |
ISBN-10: | 3540729615 |
Sprache: | Englisch |
Herstellernummer: | 11818441 |
Einband: | Gebunden |
Autor: | Rothlauf, Franz |
Hersteller: |
Springer-Verlag GmbH
Springer Berlin Heidelberg |
Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
Maße: | 241 x 160 x 20 mm |
Von/Mit: | Franz Rothlauf |
Erscheinungsdatum: | 17.07.2011 |
Gewicht: | 0,588 kg |