Solving Combinatorial Optimization Problems in Parallel Methods and Techniques Methods and Techniques

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.

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.