Solving Combinatorial Optimization Problems in Parallel [electronic resource] : Methods and Techniques / edited by Afonso Ferreira, Panos Pardalos.

By: Ferreira, Afonso [editor.]Contributor(s): Pardalos, Panos [editor.] | SpringerLink (Online service)Material type: TextTextLanguage: English Series: Lecture Notes in Computer Science: 1054Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 1996Description: VII, 280 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540498759Subject(s): Computer science | Computer aided design | Numerical analysis | Combinatorics | Management information systems | Computer Science | Computation by Abstract Devices | Numerical Analysis | Combinatorics | Business Information Systems | Systems and Information Theory in Engineering | Computer-Aided Engineering (CAD, CAE) and DesignAdditional physical formats: Printed edition:: No titleDDC classification: 004.0151 LOC classification: QA75.5-76.95Online resources: Click here to access online
Contents:
SCOOP: Solving Combinatorial Optimization problems in parallel -- Parallel approximation of optimization problems -- Randomized parallel algorithms -- Automatic synthesis of parallel algorithms -- An introduction to parallel dynamic programming -- Mapping tree-structured combinatorial optimization problems onto parallel computers -- Towards an abstract parallel branch and bound machine -- Parallel best-first branch- and-bound in discrete optimization: A framework -- Building a parallel branch and bound library -- Parallel algorithms for global optimization problems -- Parallel heuristic search — Introductions and a new approach.
In: Springer eBooksSummary: Solving combinatorial optimization problems can often lead to runtime growing exponentially as a function of the input size. But important real-world problems, industrial applications, and academic research challenges, may demand exact optimal solutions. In such situations, parallel processing can reduce the runtime from days or months, typical when one workstation is used, to a few minutes or even seconds. Partners of the CEC-sponsored SCOOP Project (Solving Combinatorial Optimization Problems in Parallel) contributed, on invitation, to this book; much attention was paid to competent coverage of the topic and the style of writing. Readers will include students, scientists, engineers, and professionals interested in the design and implementation of parallel algorithms for solving combinatorial optimization problems.
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SCOOP: Solving Combinatorial Optimization problems in parallel -- Parallel approximation of optimization problems -- Randomized parallel algorithms -- Automatic synthesis of parallel algorithms -- An introduction to parallel dynamic programming -- Mapping tree-structured combinatorial optimization problems onto parallel computers -- Towards an abstract parallel branch and bound machine -- Parallel best-first branch- and-bound in discrete optimization: A framework -- Building a parallel branch and bound library -- Parallel algorithms for global optimization problems -- Parallel heuristic search — Introductions and a new approach.

Solving combinatorial optimization problems can often lead to runtime growing exponentially as a function of the input size. But important real-world problems, industrial applications, and academic research challenges, may demand exact optimal solutions. In such situations, parallel processing can reduce the runtime from days or months, typical when one workstation is used, to a few minutes or even seconds. Partners of the CEC-sponsored SCOOP Project (Solving Combinatorial Optimization Problems in Parallel) contributed, on invitation, to this book; much attention was paid to competent coverage of the topic and the style of writing. Readers will include students, scientists, engineers, and professionals interested in the design and implementation of parallel algorithms for solving combinatorial optimization problems.

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