Parallel Algorithms For Knapsack Problems

This book brings together current research direction in the mapping of dynamic programming recurrence equations for Knapsack Type problems, which include Unbounded Knapsack Problem, 0/1 Knapsack Problem, Subset Sum Problem, Change Making Problem, onto so-called regular parallel architectures. In particular, it focuses on heuristic and more formal techniques for mapping. The text is based on substantially revised papers published by the authors and their colleagues in the literature but re-written to provide an overall view of the subject area.

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.

Mathematics of Computing -- Parallelism.

Efficient parallel solutions have been found to many problems. Some of them can be obtained automatically from sequential programs, using compilers. However, there is a large class of problems - irregular problems - that lack efficient solutions. IRREGULAR 94 - a workshop and summer school organized in Geneva - addressed the problems associated with the derivation of efficient solutions to irregular problems. This book, which is based on the workshop, draws on the contributions of outstanding scientists to present the state of the art in irregular problems, covering aspects ranging from scientific computing, discrete optimization, and automatic extraction of parallelism. Audience: This first book on parallel algorithms for irregular problems is of interest to advanced graduate students and researchers in parallel computer science.