Pardalos P. Parallel Processing of Discrete Problems 1999 torrent

Textbook in PDF format

During the last twenty years, 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.
In the context of the 1996-1997 IMA special year on Mathematics of High-Performance Computing, a workshop entitled "Parallel Processing of Discrete Problems" took place at the IMA (Institute for Mathematics and its Applications), Minneapolis on May 12-16, 1997. The topics discussed covered a wide spectrum of algorithms and applications in parallel processing of discrete optimization and related problems.
Discrete optimization problems arise in various applications, such as airline crew scheduling, corporate planning, computer-aided design and manufacturing, communications network design, machine vision, database query design, cellular telephone frequency assignment, and constraint directed reasoning. Often, a discrete optimization problem is formulated in terms of finding a least cost) solution path in a graph from an initial node to a goal node and solved by graph/tree search methods such as branch-and-bound and dynamic programming.
The search for solutions in a combinatorially large problem space is a major problem in computer science, engineering, and operations research. A general class of difficult and very important combinatorial problems include integer programming with linear or nonlinear objective function. In the worst case, such problems require solution time that grows exponentially as a function of their input size. Consequently, parallel systems, possibly with hundreds or thousands of processors, give us the perspective of efficiently solving relatively large instances of hard problems, being a motivation for using parallel processing.
The collection of refereed articles 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.
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