iterative computer algorithms de sait sadiq (16 résultats)

Paperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.4.

Etat : Good. Ships SAME or NEXT business day. We Ship to APO/FPO addr. Choose EXPEDITED shipping and receive in 2-5 business days within the United States. See our member profile for customer support contact info. We have an easy return policy.

Softcover. Etat : Bon. Ancien livre de bibliothèque. Traces d'usure sur la couverture. Edition 2000. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Signs of wear on the cover. Edition 2000. Ammareal gives back up to 15% of this item's net price to charity organizations.

Etat : As New. Unread book in perfect condition.

Etat : New.

Paperback. Etat : New. In shrink wrap. Looks like an interesting title!

Etat : New. InhaltsverzeichnisPreface. 1. Introduction. 1.1 Combinatorial Optimization. 1.2 Optimization Methods. 1.3 States, Moves, and Optimality. 1.4 Local Search. 1.5 Optimal versus Final Solution. 1.6 Single versus Multicriteria Constrained Opt.

Etat : New.

Etat : New. In.

Etat : As New. Unread book in perfect condition.

Taschenbuch. Etat : Neu. Neuware - This book examines one class of combinatorial optimization algorithms -- general iterative non-deterministic algorithms. These algorithms have recently shown significant interest due to their generality, ease of implementation, and the many success stories reporting very positive results.Iterative Computer Algorithms and Their Applications in Engineering uniformly describes five iterative algorithms for solving hard combinatorial optimization problems, namely simulated annealing, genetic algorithms, Tabu search, simulated evolution, and stochastic evolution. It is the only book to describe in a single volume these five main iterative combinatorial algorithms. The introductory chapter motivates the reader to study and use the general iterative approximation algorithms, while introducing the basic terminology.The authors present various iterative techniques and illustrate how they can be applied to solve several NP-hard problems. The book includes case studies of real engineering problems and provides comparative analysis using various techniques that the authors have experimented with and solved. For each algorithm, the authors present the procedures of the algorithm, parameter selection criteria, convergence property analysis, and parallelization. There are also several real-world examples that illustrate various aspects of the algorithms, including real engineering problems. Examples are presented wherever appropriate to illustrate any required mathematical concepts.The book has many unique features An integrated and up-to-date description of iterative non-deterministic algorithms It is the first book to describe in detail simulated evolution and stochasticevolution A brief introduction to fuzzy logic and its application in the formulation of multi-objective optimization problems A discussion on hybrid techniques that combine features of heuristics discussed in the book A level of treatment suitable for first year graduate stu.

Etat : New. pp. 410.

Etat : New. pp. 410.

Paperback. Etat : new. Paperback. Iterative Computer Algorithms with Applications in Engineering describes in-depth the five main iterative algorithms for solving hard combinatorial optimization problems: Simulated Annealing, Genetic Algorithms, Tabu Search, Simulated Evolution, and Stochastic Evolution. The authors present various iterative techniques and illustrate how they can be applied to solve several NP-hard problems. For each algorithm, the authors present the procedures of the algorithm, parameter selection criteria, convergence property analysis, and parallelization. There are also several real-world examples that illustrate various aspects of the algorithms. The book includes an introduction to fuzzy logic and its application in the formulation of multi-objective optimization problems, a discussion on hybrid techniques that combine features of heuristics, a survey of recent research work, and examples that illustrate required mathematical concepts. The unique features of this book are: An integrated and up-to-date description of iterative non-deterministic algorithms; Detailed descriptions of Simulated Evolution and Stochastic Evolution; A level of treatment suitable for first year graduate student and practicing engineers; Parallelization aspects and particular parallel implementations; A brief survey of recent research work; Graded exercises and an annotated bibliography in each chapter This work uniformly describes five iterative algorithms for solving hard combinatorial optimization problems, namely simulated annealing, genetic algorithms, Tabu search, simulated evolution, and stochastic evolution. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Etat : new. Paperback. Iterative Computer Algorithms with Applications in Engineering describes in-depth the five main iterative algorithms for solving hard combinatorial optimization problems: Simulated Annealing, Genetic Algorithms, Tabu Search, Simulated Evolution, and Stochastic Evolution. The authors present various iterative techniques and illustrate how they can be applied to solve several NP-hard problems. For each algorithm, the authors present the procedures of the algorithm, parameter selection criteria, convergence property analysis, and parallelization. There are also several real-world examples that illustrate various aspects of the algorithms. The book includes an introduction to fuzzy logic and its application in the formulation of multi-objective optimization problems, a discussion on hybrid techniques that combine features of heuristics, a survey of recent research work, and examples that illustrate required mathematical concepts. The unique features of this book are: An integrated and up-to-date description of iterative non-deterministic algorithms; Detailed descriptions of Simulated Evolution and Stochastic Evolution; A level of treatment suitable for first year graduate student and practicing engineers; Parallelization aspects and particular parallel implementations; A brief survey of recent research work; Graded exercises and an annotated bibliography in each chapter This work uniformly describes five iterative algorithms for solving hard combinatorial optimization problems, namely simulated annealing, genetic algorithms, Tabu search, simulated evolution, and stochastic evolution. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 633.