Operations Research emerged as a quantitative approach to problem-solving in World War II. Its founders, who were physicists, mathematicians, and engineers, quickly found peace-time uses for this new field. Moreover, we can say that Operations Research (OR) was born in the same incubator as computer science, and through the years, it has spawned many new disciplines, including systems engineering, health care management, and transportation science. Fundamentally, Operations Research crosses discipline domains to seek solutions on a range of problems and benefits diverse disciplines from finance to bioengineering. Many disciplines routinely use OR methods. Many scientific researchers, engineers, and others will find the methodological presentations in this book useful and helpful in their problem-solving efforts. OR's strengths are modeling, analysis, and algorithm design. It provides a quantitative foundation for a broad spectrum of problems, from economics to medicine, from environmental control to sports, from e-commerce to computational geometry.

"The primary purpose of Tutorials on Emerging Methodologies and Applications in Operations Research is to provide a reference for practitioners and academics who seek a clear, concise presentation of developing methodologies, hence providing themselves with the capability to apply these methods to new problems. The field of Operations Research is always changing. Its changes are driven by the technology it uses and that it extends, and the applications that it affects. Relevant changes in the field have a permanent effect on the conduct of OR and are vital to anyone who wants to be current in the field.

Heuristic Search for Network Design.- Polyhedral Combinatorics.- Constraint Languages for Combinatorial Optimization.- A Tutorial on Radiation Oncology and Optimization.- Parallel Algorithm Design for Branch and Bound.- Computer-Aided Design for Electrical and Computer engineering.- Nonlinear Programming and Engineering Applications.- Connecting MRP, MRP II and ERP - Supply Chain Production Planning Via Optimization Models.