Distributed branch and bound algorithms for global optimization.- Large-scale structured discrete optimization via parallel genetic algorithms.- Pushing the limits of solvable QAP problems using parallel processing - is Nugent30 within reach?.- On the design of parallel discrete algorithms for high performance computing systems.- Parallel algorithms for satisfiability (SAT) testing.- Sequential and parallel branch-and-bound search under limited-memory constraints.- A parallel grasp for the data association multidimensional assignment problem.- Basic algorithms on parallel optical models of computing.- Randomized parallel algorithms.- Finite behavior of simulated annealing: A probabilistic study.
In the past two decades, breakthroughs in computer technology have made a tremendous impact on optimization. In particular, availability of parallel computers has created substantial interest in exploring the use of parallel processing for solving discrete and global optimization problems. The chapters in this volume cover a broad spectrum of recent research in parallel processing of discrete and related problems. The topics discussed include distributed branch-and-bound algorithms, parallel genetic algorithms for large scale discrete problems, simulated annealing, parallel branch-and-bound search under limited-memory constraints, parallelization of greedy randomized adaptive search procedures, parallel optical models of computing, randomized parallel algorithms, general techniques for the design of parallel discrete algorithms, parallel algorithms for the solution of quadratic assignment and satisfiability problems. The book will be a valuable source of information to faculty, students and researchers in combinatorial optimization and related areas.
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