Using a wide range of operational research (OR) optimization examples, Applied Operational Research with SAS demonstrates how the OR procedures in SAS work. The book is one of the first to extensively cover the application of SAS procedures to OR problems, such as single criterion optimization, project management decisions, printed circuit board assembly, and multiple criteria decision making.
The text begins with the algorithms and methods for linear programming, integer linear programming, and goal programming models. It then describes the principles of several OR procedures in SAS. Subsequent chapters explain how to use these procedures to solve various types of OR problems. Each of these chapters describes the concept of an OR problem, presents an example of the problem, and discusses the specific procedure and its macros for the optimal solution of the problem. The macros include data handling, model building, and report writing.
While primarily designed for SAS users in OR and marketing analytics, the book can also be used by readers interested in mathematical modeling techniques. By formulating the OR problems as mathematical models, the authors show how SAS can solve a variety of optimization problems.
Table of Contents
Operational Research, Algorithms, and Methods
Integer Linear Programming
SAS for Operational Research including PROC OPTMODEL
Minimum-Cost Capacitated Flow Problem
Maximum Flow Problem
Shortest Path Problem
Critical Path Analysis
Program Evaluation and Review Technique (PERT)
Assembly Line-Balancing Problem
Traveling Salesman Problem
Traveling Salesman Problem (TSP)
Printed Circuit Board Production Planning
Printed Circuit Board (PCB) Assembly Line Assignment Problem
PCB Component Allocation Problem
PCB Component-Sequencing Problem for PAP Machines
Multiple-Criteria Decision Making
Multiple-Criteria Logistics Distribution Problem: Analytic Hierarchy Process
Multiple-Criteria Logistics Distribution Problem: Logistics Distribution Network
Decision Making and Efficiency Measurement
Multiple-Criteria Preference Ranking: Ordered Weighted Averaging (OWA)
Efficiency Measurement: Data Envelopment Analysis (DEA)
Productivity Measurement: Nonparametric Malmquist Index
Ali Emrouznejad is a reader in the Operations & Information Management Group at Aston Business School. Dr. Emrouznejad is a senior editor and one of the founding members of the Data Envelopment Analysis Journal and an associate editor of the IMA Journal of Management Mathematics. He is also co-founder of Performance Improvement Management Software (PIM-DEA) and maintains a website for DEA users at www.deazone.com He earned a Ph.D. in operational research and systems from Warwick Business School. His research interests include performance measurement and management, efficiency and productivity analysis, and data mining.
William Ho is the BAM course director and a senior lecturer in the Operations & Information Management Group at Aston Business School. Dr. Ho is an editorial board member of the International Journal of Advanced Manufacturing Technology and an associate editor of OR Insights. He earned a Ph.D. in operations research from the Hong Kong Polytechnic University. His research interests include supply chain management, transportation and logistics management, production and operations management, and operations research.
Featured Author Profiles
"… the authors do a good job of explaining how to apply SAS to a wide variety of problems in operations research and operations management, and the publisher makes copies of SAS code from the book available to purchasers of the book. For the reader who has a sufficient background in operations research, is comfortable with SAS macros, and is interested in learning, this book will provide a welcome and useful resource."
—The American Statistician, August 2014
"This book successfully bridges the gap between theory and practice. Written primarily for SAS, the authors present a wide range of optimisation problems to demonstrate how the SAS/OR® procedures work. The text is well written, easy to follow, and will appeal both to those who have an interest only in concepts and to those merely interested in solving practical problems."
—Carl M. O’Brien, International Statistical Review (2013), 81
Link for codes and datasets
click on http://www.sas-or.com/