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Condition: New. pp. 238 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
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Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics: International Workshop, SLS 2009, ... (Lecture Notes in Computer Science, 5752)
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Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics: International Workshop, SLS 2007, ... (Lecture Notes in Computer Science, 4638)
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Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics : International Workshop, SLS 2009, Brussels, Belgium, September 3-5, 2009, Proceedings
Published by Springer Berlin Heidelberg, 2009
ISBN 10: 364203750X ISBN 13: 9783642037504
Language: English
£ 47.99
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Stochastic local search (SLS) algorithms are established tools for the solution of computationally hard problems arising in computer science, business adm- istration, engineering, biology, and various other disciplines. To a large extent, their success is due to their conceptual simplicity, broad applicability and high performance for many important problems studied in academia and enco- tered in real-world applications. SLS methods include a wide spectrum of te- niques, ranging from constructive search procedures and iterative improvement algorithms to more complex SLS methods, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search, and variable neighborhood search. Historically, the development of e ective SLS algorithms has been guided to a large extent by experience and intuition. In recent years, it has become - creasingly evident that success with SLS algorithms depends not merely on the adoption and e cient implementation of the most appropriate SLS technique for a given problem, but also on the mastery of a more complex algorithm - gineering process. Challenges in SLS algorithm development arise partly from the complexity of the problems being tackled and in part from the many - grees of freedom researchers and practitioners encounter when developing SLS algorithms. Crucial aspects in the SLS algorithm development comprise al- rithm design, empirical analysis techniques, problem-speci c background, and background knowledge in several key disciplines and areas, including computer science, operations research, arti cial intelligence, and statistics.
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Engineering Stochastic Local Search Algorithms
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2009
ISBN 10: 364203750X ISBN 13: 9783642037504
Language: English
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Add to basketCondition: New. Series: Lecture Notes in Computer Science / Theoretical Computer Science and General Issues. Num Pages: 165 pages, biography. BIC Classification: UMB. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 10. Weight in Grams: 266. . 2009. Paperback. . . . .
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Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics: International Workshop, SLS 2007, Brussels
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Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics : International Workshop, SLS 2007, Brussels, Belgium, September 6-8, 2007, Proceedings
Published by Springer, Berlin, Springer Berlin Heidelberg, Springer, 2007
ISBN 10: 3540744452 ISBN 13: 9783540744450
Language: English
£ 51.75
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Stochastic local search (SLS) algorithms enjoy great popularity as powerful and versatile tools for tackling computationally hard decision and optimization pr- lems from many areas of computer science, operations research, and engineering. To a large degree, this popularity is based on the conceptual simplicity of many SLS methods and on their excellent performance on a wide gamut of problems, ranging from rather abstract problems of high academic interest to the very s- ci c problems encountered in many real-world applications. SLS methods range from quite simple construction procedures and iterative improvement algorithms to more complex general-purpose schemes, also widely known as metaheuristics, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search and variable neighborhood search. Historically, the development of e ective SLS algorithms has been guided to a large extent by experience and intuition, and overall resembled more an art than a science. However, in recent years it has become evident that at the core of this development task there is a highly complex engineering process, which combines various aspects of algorithm design with empirical analysis techniques and problem-speci c background, and which relies heavily on knowledge from a number of disciplines and areas, including computer science, operations research, arti cial intelligence, and statistics. This development process needs to be - sisted by a sound methodology that addresses the issues arising in the various phases of algorithm design, implementation, tuning, and experimental eval- tion.
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Add to basketPaperback. Condition: Very Good. We are unable to ship to Canada at this time.Ex-library paperback in very nice condition with the usual markings and attachments.
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Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics: International Workshop, Sls 2009, Brussels, Belgium, September 3-5, 2009, Proceedings: Vol 5752
Published by Springer-Verlag New York Inc, 2009
ISBN 10: 364203750X ISBN 13: 9783642037504
Language: English
Paperback. Condition: Brand New. 2009 edition. 155 pages. 9.00x6.00x0.50 inches. In Stock.
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Engineering Stochastic Local Search Algorithms: Designing, Implementing and Analyzing Effective Heuristics, International Workshop, SLS 2007 Brussels, Belgium, September 6-8, 2007 Proceedings
Published by Springer-Verlag New York Inc, 2007
ISBN 10: 3540744452 ISBN 13: 9783540744450
Language: English
Paperback. Condition: Brand New. 1st edition. 221 pages. 9.00x6.00x0.50 inches. In Stock.
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Engineering Stochastic Local Search Algorithms
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2009
ISBN 10: 364203750X ISBN 13: 9783642037504
Language: English
£ 73.28
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Add to basketCondition: New. Series: Lecture Notes in Computer Science / Theoretical Computer Science and General Issues. Num Pages: 165 pages, biography. BIC Classification: UMB. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 10. Weight in Grams: 266. . 2009. Paperback. . . . . Books ship from the US and Ireland.
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Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics (Paperback)
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2007
ISBN 10: 3540744452 ISBN 13: 9783540744450
Language: English
£ 53.49
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Add to basketPaperback. Condition: new. Paperback. Stochastic local search (SLS) algorithms enjoy great popularity as powerful and versatile tools for tackling computationally hard decision and optimization pr- lems from many areas of computer science, operations research, and engineering. To a large degree, this popularity is based on the conceptual simplicity of many SLS methods and on their excellent performance on a wide gamut of problems, ranging from rather abstract problems of high academic interest to the very s- ci?c problems encountered in many real-world applications. SLS methods range from quite simple construction procedures and iterative improvement algorithms to more complex general-purpose schemes, also widely known as metaheuristics, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search and variable neighborhood search. Historically, the development of e?ective SLS algorithms has been guided to a large extent by experience and intuition, and overall resembled more an art than a science. However, in recent years it has become evident that at the core of this development task there is a highly complex engineering process, which combines various aspects of algorithm design with empirical analysis techniques and problem-speci?c background, and which relies heavily on knowledge from a number of disciplines and areas, including computer science, operations research, arti?cial intelligence, and statistics. This development process needs to be - sisted by a sound methodology that addresses the issues arising in the various phases of algorithm design, implementation, tuning, and experimental eval- tion. Stochastic local search (SLS) algorithms enjoy great popularity as powerful and versatile tools for tackling computationally hard decision and optimization pr- lems from many areas of computer science, operations research, and engineering. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics (Paperback)
Published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, Berlin, 2009
ISBN 10: 364203750X ISBN 13: 9783642037504
Language: English
£ 53.49
Convert currency£ 37.10 shipping from U.S.A. to United KingdomQuantity: 1 available
Add to basketPaperback. Condition: new. Paperback. Stochastic local search (SLS) algorithms are established tools for the solution of computationally hard problems arising in computer science, business adm- istration, engineering, biology, and various other disciplines. To a large extent, their success is due to their conceptual simplicity, broad applicability and high performance for many important problems studied in academia and enco- tered in real-world applications. SLS methods include a wide spectrum of te- niques, ranging from constructive search procedures and iterative improvement algorithms to more complex SLS methods, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search, and variable neighborhood search. Historically, the development of e?ective SLS algorithms has been guided to a large extent by experience and intuition. In recent years, it has become - creasingly evident that success with SLS algorithms depends not merely on the adoption and e?cient implementation of the most appropriate SLS technique for a given problem, but also on the mastery of a more complex algorithm - gineering process. Challenges in SLS algorithm development arise partly from the complexity of the problems being tackled and in part from the many - grees of freedom researchers and practitioners encounter when developing SLS algorithms. Crucial aspects in the SLS algorithm development comprise al- rithm design, empirical analysis techniques, problem-speci?c background, and background knowledge in several key disciplines and areas, including computer science, operations research, arti?cial intelligence, and statistics. SLS methods include a wide spectrum of te- niques, ranging from constructive search procedures and iterative improvement algorithms to more complex SLS methods, such as ant colony optimization, evolutionary computation, iterated local search, memetic algorithms, simulated annealing, tabu search, and variable neighborhood search. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
