In applied mathematics and computer science, combinatorial optimization algorithms solve problems that are believed to be hard in general, by exploring the usually large solution search space of the problem, then reducing its effective size and exploring it efficiently. Researchers from Europe, the Americas, and Japan explore exact algorithms, metaheuristics, hybrid approaches using both, and multi-objective optimization algorithms. They also consider frameworks and libraries that integrate parallel algorithms for combinatorial optimization. Annotation ©2006 Book News, Inc., Portland, OR (booknews.com)
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.
