Parallel Metaheuristics – A New Class of Algorithms

Providing a single reference on parallel metaheuristic issues, this comprehensive book presents modern and ongoing research information on using, designing, and analyzing efficient models of parallel algorithms (numeric and real-time efficiency, algorithms, comparison of parallel models).

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With the proliferation of parallel computers and faster community networks, parallel metaheuristics are an effective alternative to speed up the search for approximate solutions of optimizations problems and allow solving larger problems while leading to more efficient algorithms. "Parallel Metaheuristics" provides a single, up-to-date reference on parallel metaheuristic issues: Edited single source to fill a gap on metaheuristics by discussing parallelism (contributors are authors of outstanding cutting-edge works in the field); Includes sequential and parallel techniques, up-to-date modern optimization and learning procedures, and complex applications; Real-world problem solutions throughout; and for researchers in the field and with introductory parts suited for beginners.