Parallel Combinatorial Optimization

Parallel Combinatorial Optimization

This text provides an excellent balance of theory and application that enables you to deploy powerful algorithms, frameworks, and methodologies to solve complex optimization problems in a diverse range of industries. Each chapter is written by leading experts in the fields of parallel and distributed optimization. Collectively, the contributions serve as a complete reference to the field of combinatorial optimization, including details and findings of recent and ongoing investigations.

Solving Combinatorial Optimization Problems in Parallel

Methods and Techniques

Solving Combinatorial Optimization Problems in Parallel

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.

Solving Combinatorial Optimization Problems in Parallel

Methods and Techniques

Solving Combinatorial Optimization Problems in Parallel

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.

Applications of Combinatorial Optimization

Applications of Combinatorial Optimization

Combinatorial optimization is a multidisciplinary scientific area,lying in the interface of three major scientific domains:mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aimsto cover a wide range of topics in this area. These topics alsodeal with fundamental notions and approaches as with severalclassical applications of combinatorial optimization. “Applications of Combinatorial Optimization” ispresenting a certain number among the most common and well-knownapplications of Combinatorial Optimization.

Concepts of Combinatorial Optimization

Concepts of Combinatorial Optimization

Combinatorial optimization is a multidisciplinary scientific area,lying in the interface of three major scientific domains:mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimizationseries aims to cover a wide range of topics in this area. Thesetopics also deal with fundamental notions and approaches as withseveral classical applications of combinatorial optimization. Concepts of Combinatorial Optimization, is divided intothree parts: On the complexity of combinatorial optimization problems, thatpresents basics about worst-case and randomized complexity; Classical solution methods, that presents the two most-knownmethods for solving hard combinatorial optimization problems, thatare Branch-and-Bound and Dynamic Programming; Elements from mathematical programming, that presentsfundamentals from mathematical programming based methods that arein the heart of Operations Research since the origins of thisfield.

Surveys in Combinatorial Optimization

Surveys in Combinatorial Optimization

A collection of papers surveying recent progress in the field of Combinatorial Optimization. Topics examined include theoretical and computational aspects (Boolean Programming, Probabilistic Analysis of Algorithms, Parallel Computer Models and Combinatorial Algorithms), well-known combinatorial problems (such as the Linear Assignment Problem, the Quadratic Assignment Problem, the Knapsack Problem and Steiner Problems in Graphs) and more applied problems (such as Network Synthesis and Dynamic Network Optimization, Single Facility Location Problems on Networks, the Vehicle Routing Problem and Scheduling Problems).

Recent Advances in Parallel Virtual Machine and Message Passing Interface

14th European PVM/MPI User's Group Meeting, Paris France, September 30 - October 3, 2007, Proceedings

Recent Advances in Parallel Virtual Machine and Message Passing Interface

This book constitutes the refereed proceedings of the 14th European PVM/MPI Users' Group Meeting held in Paris, France, September 30 - October 3, 2007. The 40 revised full papers presented together with abstracts of six invited contributions, three tutorial papers and six poster papers were carefully reviewed and selected from 68 submissions. The papers are organized in topical sections.

Integration of AI and OR Techniques in Constraint Programming

11th International Conference, CPAIOR 2014, Cork, Ireland, May 19-23, 2014, Proceedings

Integration of AI and OR Techniques in Constraint Programming

This book constitutes the proceedings of the International Conference on the Integration of Artificial Intelligence (AI) and Operations Research (OR) Techniques in Constraint Programming, CPAIOR 2014, held in Cork, Ireland, in May 2014. The 33 papers presented in this volume were carefully reviewed and selected from 70 submissions. The papers focus on constraint programming and global constraints; scheduling modelling; encodings and SAT logistics; MIP; CSP and complexity; parallelism and search; and data mining and machine learning.

Parallel Processing of Discrete Optimization Problems

DIMACS Workshop, April 28-29, 1994

Parallel Processing of Discrete Optimization Problems

This book contains papers presented at the Workshop on Parallel Processing of Discrete Optimization Problems held at DIMACS in April 1994. The contents cover a wide spectrum of the most recent algorithms and applications in parallel processing of discrete optimization and related problems. Topics include parallel branch and bound algorithms, scalability, load balancing, parallelism and irregular data structures and scheduling task graphs on parallel machines. Applications include parallel algorithms for solving satisfiability problems, location problems, linear programming, quadratic and linear assignment problems. This book would be suitable as a textbook in advanced courses on parallel algorithms and combinatorial optimization.