Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics: Second International Workshop, SLS 2009 ... 5752 (Lecture Notes in Computer Science) - Softcover

 
9783642037504: Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics: Second International Workshop, SLS 2009 ... 5752 (Lecture Notes in Computer Science)
Softcover
ISBN 10: 364203750X ISBN 13: 9783642037504
Verlag: Springer, 2009

Inhaltsangabe

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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Reseña del editor

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.

Reseña del editor

This book constitutes the refereed proceedings of the International Workshop on Engineering Stochastic Local Search Algorithms 2009, held in Brussels, Belgium, September 3-5, 2009. The 7 revised full papers presented together with 10 short papers were carefully reviewed and selected from more than 27 submissions. The topics include e. g. the use of run time distributions to evaluate and compare, high- performance local search for task scheduling with human, running time analysis of ACO Systems for shortest path problems, the explorative behavior of MAX-MIN ant system and improved robustness through population variance and colony optimization.

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Verlag
Springer
Erscheinungsdatum
2009
Sprache
Englisch
ISBN 10 
364203750X
ISBN 13 
9783642037504
Einband
Tapa blanda
Anzahl der Seiten
168
Herausgeber
Stutzle Thomas
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
CMN Printpool Inh. Mathis Neumann
https://www.also.com/ec/cms5/en_6000/6000/index.jsp

Friedrich-Karl-Str. 9
Hamburg
Deutschland

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9783642037528: Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics

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ISBN 10:  3642037526 ISBN 13:  9783642037528
Verlag: Springer, 2009
Softcover