Parallel Metaheuristics: A New Class of AlgorithmsJohn Wiley & Sons, 2005. gada 3. okt. - 565 lappuses Solving complex optimization problems with parallel metaheuristics Parallel Metaheuristics brings together an international group of experts in parallelism and metaheuristics to provide a much-needed synthesis of these two fields. Readers discover how metaheuristic techniques can provide useful and practical solutions for a wide range of problems and application domains, with an emphasis on the fields of telecommunications and bioinformatics. This volume fills a long-existing gap, allowing researchers and practitioners to develop efficient metaheuristic algorithms to find solutions. The book is divided into three parts: * Part One: Introduction to Metaheuristics and Parallelism, including an Introduction to Metaheuristic Techniques, Measuring the Performance of Parallel Metaheuristics, New Technologies in Parallelism, and a head-to-head discussion on Metaheuristics and Parallelism * Part Two: Parallel Metaheuristic Models, including Parallel Genetic Algorithms, Parallel Genetic Programming, Parallel Evolution Strategies, Parallel Ant Colony Algorithms, Parallel Estimation of Distribution Algorithms, Parallel Scatter Search, Parallel Variable Neighborhood Search, Parallel Simulated Annealing, Parallel Tabu Search, Parallel GRASP, Parallel Hybrid Metaheuristics, Parallel Multi-Objective Optimization, and Parallel Heterogeneous Metaheuristics * Part Three: Theory and Applications, including Theory of Parallel Genetic Algorithms, Parallel Metaheuristics Applications, Parallel Metaheuristics in Telecommunications, and a final chapter on Bioinformatics and Parallel Metaheuristics Each self-contained chapter begins with clear overviews and introductions that bring the reader up to speed, describes basic techniques, and ends with a reference list for further study. Packed with numerous tables and figures to illustrate the complex theory and processes, this comprehensive volume also includes numerous practical real-world optimization problems and their solutions. This is essential reading for students and researchers in computer science, mathematics, and engineering who deal with parallelism, metaheuristics, and optimization in general. |
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applications approach Artificial assignment problem best solution cellular classification colony combinatorial optimization communication Computer Science configuration cooperative Crainic defined diversification EDAs editors evaluation evolution strategies Evolutionary Algorithms Evolutionary Computation exchange field find first fitness fixed function Gendreau Genetic Algorithms global grid heterogeneous heuristic hybrid IEEE individuals island Journal master-slave method migration Morgan Kaufmann Multiobjective multiobjective optimization neighbors network design nodes number of iterations number of processors Operations Research optimization problems p-median problem Parallel and Distributed Parallel Computing Parallel Genetic Algorithms parallel implementations parallel metaheuristics parallel models Parallel Tabu Search parallelization strategies parameters partitioning performed pheromone population Proc procedure Proceedings proposed Quadratic Assignment Problem random Resende Ribeiro Scatter Search search space search threads selection sequences sequential Simulated Annealing slave solution quality solve specific speedup structure subpopulations subset synchronous Tabu Search topology Traveling Salesman Problem update values Vehicle Routing Problem
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Atsauces uz šo grāmatu
Masterkurs Parallele und Verteilte Systeme: Grundlagen und Programmierung ... Christian Baun,Marcel Kunze,Karl-Uwe Stucky Priekšskatījums nav pieejams - 2008 |