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Design of Heuristic Algorithms for Hard Optimization
With Python Codes for the Travelling Salesman Problem
Buch von Éric D. Taillard
Sprache: Englisch

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Beschreibung
This open access book demonstrates all the steps required to design heuristic algorithms for difficult optimization. The classic problem of the travelling salesman is used as a common thread to illustrate all the techniques discussed. This problem is ideal for introducing readers to the subject because it is very intuitive and its solutions can be graphically represented. The book features a wealth of illustrations that allow the concepts to be understood at a glance.

The book approaches the main metaheuristics from a new angle, deconstructing them into a few key concepts presented in separate chapters: construction, improvement, decomposition, randomization and learning methods. Each metaheuristic can then be presented in simplified form as a combination of these concepts. This approach avoids giving the impression that metaheuristics is a non-formal discipline, a kind of cloud sculpture. Moreover, it provides concrete applications of the travelling salesman problem, whichillustrate in just a few lines of code how to design a new heuristic and remove all ambiguities left by a general framework. Two chapters reviewing the basics of combinatorial optimization and complexity theory make the book self-contained. As such, even readers with a very limited background in the field will be able to follow all the content.
This open access book demonstrates all the steps required to design heuristic algorithms for difficult optimization. The classic problem of the travelling salesman is used as a common thread to illustrate all the techniques discussed. This problem is ideal for introducing readers to the subject because it is very intuitive and its solutions can be graphically represented. The book features a wealth of illustrations that allow the concepts to be understood at a glance.

The book approaches the main metaheuristics from a new angle, deconstructing them into a few key concepts presented in separate chapters: construction, improvement, decomposition, randomization and learning methods. Each metaheuristic can then be presented in simplified form as a combination of these concepts. This approach avoids giving the impression that metaheuristics is a non-formal discipline, a kind of cloud sculpture. Moreover, it provides concrete applications of the travelling salesman problem, whichillustrate in just a few lines of code how to design a new heuristic and remove all ambiguities left by a general framework. Two chapters reviewing the basics of combinatorial optimization and complexity theory make the book self-contained. As such, even readers with a very limited background in the field will be able to follow all the content.
Über den Autor
Éric D. Taillard is a professor at the University of Applied Sciences and Arts of Western Switzerland, HEIG-VD campus in Yverdon-les-Bains. After completing his studies and obtaining a PhD at the Swiss Federal Institute of Technology in Lausanne, he worked as a researcher at the Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation in Montreal, Canada, and then at the Dalle Molle Institute for Artificial Intelligence in Lugano, Switzerland.
He has over 30 years of research experience in the field of metaheuristics. Outside of Switzerland, he has been invited to teach this subject at various universities: Vienna and Graz in Austria, Nantes in France and Hamburg in Germany.
Zusammenfassung

This book is open access, which means that you have free and unlimited access

Offers step-by-step procedures for the design of heuristic algorithms

Contains numerous short illustrative codes for the travelling salesman problem

Covers the main metaheuristics in a simple but rigorous way

Inhaltsverzeichnis
Part I: Combinatorial Optimization, Complexity Theory and Problem Modelling.- 1. Elements of Graphs and Complexity Theory.- 2. A Short List of Combinatorial Optimization Problems.- 3. Problem Modelling.- Part II: Basic Heuristic Techniques.- 4. Constructive Methods.- 5. Local Search.- 6. Decomposition Methods.- Part III: Popular Metaheuristics.- 7. Randomized Methods.- 8. Construction Learning.- 9. Local Search Learning.- 10. Population Management.- 11. Heuristics Design.- 12. Codes.
Details
Erscheinungsjahr: 2022
Fachbereich: Allgemeines
Genre: Recht, Sozialwissenschaften, Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Buch
Reihe: Graduate Texts in Operations Research
Inhalt: xv
287 S.
1 s/w Illustr.
287 p. 1 illus. With online files/update.
ISBN-13: 9783031137136
ISBN-10: 3031137132
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Taillard, Éric D.
Auflage: 1st ed. 2023
Hersteller: Springer International Publishing
Graduate Texts in Operations Research
Verantwortliche Person für die EU: Books on Demand GmbH, In de Tarpen 42, D-22848 Norderstedt, info@bod.de
Maße: 241 x 160 x 22 mm
Von/Mit: Éric D. Taillard
Erscheinungsdatum: 30.10.2022
Gewicht: 0,623 kg
Artikel-ID: 122078797
Über den Autor
Éric D. Taillard is a professor at the University of Applied Sciences and Arts of Western Switzerland, HEIG-VD campus in Yverdon-les-Bains. After completing his studies and obtaining a PhD at the Swiss Federal Institute of Technology in Lausanne, he worked as a researcher at the Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation in Montreal, Canada, and then at the Dalle Molle Institute for Artificial Intelligence in Lugano, Switzerland.
He has over 30 years of research experience in the field of metaheuristics. Outside of Switzerland, he has been invited to teach this subject at various universities: Vienna and Graz in Austria, Nantes in France and Hamburg in Germany.
Zusammenfassung

This book is open access, which means that you have free and unlimited access

Offers step-by-step procedures for the design of heuristic algorithms

Contains numerous short illustrative codes for the travelling salesman problem

Covers the main metaheuristics in a simple but rigorous way

Inhaltsverzeichnis
Part I: Combinatorial Optimization, Complexity Theory and Problem Modelling.- 1. Elements of Graphs and Complexity Theory.- 2. A Short List of Combinatorial Optimization Problems.- 3. Problem Modelling.- Part II: Basic Heuristic Techniques.- 4. Constructive Methods.- 5. Local Search.- 6. Decomposition Methods.- Part III: Popular Metaheuristics.- 7. Randomized Methods.- 8. Construction Learning.- 9. Local Search Learning.- 10. Population Management.- 11. Heuristics Design.- 12. Codes.
Details
Erscheinungsjahr: 2022
Fachbereich: Allgemeines
Genre: Recht, Sozialwissenschaften, Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Buch
Reihe: Graduate Texts in Operations Research
Inhalt: xv
287 S.
1 s/w Illustr.
287 p. 1 illus. With online files/update.
ISBN-13: 9783031137136
ISBN-10: 3031137132
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Autor: Taillard, Éric D.
Auflage: 1st ed. 2023
Hersteller: Springer International Publishing
Graduate Texts in Operations Research
Verantwortliche Person für die EU: Books on Demand GmbH, In de Tarpen 42, D-22848 Norderstedt, info@bod.de
Maße: 241 x 160 x 22 mm
Von/Mit: Éric D. Taillard
Erscheinungsdatum: 30.10.2022
Gewicht: 0,623 kg
Artikel-ID: 122078797
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