Profiles In Operations Research

Profiles in Operations Research: Pioneers and Innovators recounts the development of the field of Operations Research (OR), the science of decision making. The book traces the development of OR from its military origins to a mature discipline that is recognized worldwide for its contributions to managerial planning and complex global operations. Over the past six decades, OR analyses have impacted our daily lives: when making an airline or hotel reservation, waiting in line at a bank, getting the correctly blended fuel at the gas station, and ensuring that the book you are holding arrived at its destination on time. OR originated in the late 1930s when British scientists from various disciplines joined Royal Air Force officers to determine the most effective way to employ new radar technology for intercepting enemy aircraft. During World War II, similar applied research groups were formed to study, test, and evaluate military operations on both sides of the Atlantic. Their work resulted in great improvements—OR helped the Allies win the war. The scientific field that emerged from these studies was called operational research in the U.K. and operations research in the U.S. Today, OR provides a broad and powerful science to aid decision making. Profiles describes the lives and contributions of 43 OR pioneers and innovators and relates how these individuals, with varying backgrounds and diverse interests, were drawn to the nascent field of OR. The profiles also describe how OR techniques and applications expanded considerably beyond the military context to find new domains in business and industry. In addition to their scientific contributions, these profiles capture the life stories of the individuals—interwoven with personal tales, vivid vignettes, family backgrounds, and views of the mission and future of OR. Collectively, the profiles recount the fascinating story of the growth and development of a field enriched by the convergence of different disciplines. The Editors: Arjang A. Assad is Dean of the School of Management, University at Buffalo, State University of New York. Saul I. Gass is Professor Emeritus, Department of Decision, Operations & Information Technologies, Smith School of Business, University of Maryland, College Park. From the Reviews Profiles In Operations Research: Pioneers and Innovators. Book Review by Nigel Cummings: U.K. OR Society's e-journal, Inside OR., Sept 2011. "I can thoroughly recommend this book. I found it both enlighteningand undeniably gripping, so much so in fact, you may find it difficultto put it down once you have commenced reading it. Arjang A. Assad and Saul I. Gass have created a masterwork whichwill serve to immortalise [stet] the pioneers of O.R. for many years to come." *For a list of all known typos, plus further discussion on the book, please visit http://profilesinoperationsresearch.com.

Operations Research: A Practical Introduction is just that: a hands-on approach to the field of operations research (OR) and a useful guide for using OR techniques in scientific decision making, design, analysis and management. The text accomplishes two goals. First, it provides readers with an introduction to standard mathematical models and algorithms. Second, it is a thorough examination of practical issues relevant to the development and use of computational methods for problem solving. Highlights: All chapters contain up-to-date topics and summaries A succinct presentation to fit a one-term course Each chapter has references, readings, and list of key terms Includes illustrative and current applications New exercises are added throughout the text Software tools have been updated with the newest and most popular software Many students of various disciplines such as mathematics, economics, industrial engineering and computer science often take one course in operations research. This book is written to provide a succinct and efficient introduction to the subject for these students, while offering a sound and fundamental preparation for more advanced courses in linear and nonlinear optimization, and many stochastic models and analyses. It provides relevant analytical tools for this varied audience and will also serve professionals, corporate managers, and technical consultants.

In both rich and poor nations, public resources for health care are inadequate to meet demand. Policy makers and health care providers must determine how to provide the most effective health care to citizens using the limited resources that are available. This chapter describes current and future challenges in the delivery of health care, and outlines the role that operations research (OR) models can play in helping to solve those problems. The chapter concludes with an overview of this book – its intended audience, the areas covered, and a description of the subsequent chapters. KEY WORDS Health care delivery, Health care planning HEALTH CARE DELIVERY: PROBLEMS AND CHALLENGES 3 1.1 WORLDWIDE HEALTH: THE PAST 50 YEARS Human health has improved significantly in the last 50 years. In 1950, global life expectancy was 46 years [1]. That figure rose to 61 years by 1980 and to 67 years by 1998 [2]. Much of these gains occurred in low- and middle-income countries, and were due in large part to improved nutrition and sanitation, medical innovations, and improvements in public health infrastructure.

The breadth of information about operations research and the overwhelming size of previous sources on the subject make it a difficult topic for non-specialists to grasp. Fortunately, Introduction to the Mathematics of Operations Research with Mathematica®, Second Edition delivers a concise analysis that benefits professionals in operations research and related fields in statistics, management, applied mathematics, and finance. The second edition retains the character of the earlier version, while incorporating developments in the sphere of operations research, technology, and mathematics pedagogy. Covering the topics crucial to applied mathematics, it examines graph theory, linear programming, stochastic processes, and dynamic programming. This self-contained text includes an accompanying electronic version and a package of useful commands. The electronic version is in the form of Mathematica notebooks, enabling you to devise, edit, and execute/reexecute commands, increasing your level of comprehension and problem-solving. Mathematica sharpens the impact of this book by allowing you to conveniently carry out graph algorithms, experiment with large powers of adjacency matrices in order to check the path counting theorem and Markov chains, construct feasible regions of linear programming problems, and use the "dictionary" method to solve these problems. You can also create simulators for Markov chains, Poisson processes, and Brownian motions in Mathematica, increasing your understanding of the defining conditions of these processes. Among many other benefits, Mathematica also promotes recursive solutions for problems related to first passage times and absorption probabilities.

Probabilistic modeling represents a subject spanning many branches of mathematics, economics, and computer science to connect pure mathematics with applied sciences. Operational research also relies on this connection to enable the improvement of business functions and decision making. Analyzing Risk through Probabilistic Modeling in Operations Research is an authoritative reference publication discussing the various challenges in management and decision science. Featuring exhaustive coverage on a range of topics within operational research including, but not limited to, decision analysis, data mining, process modeling, probabilistic interpolation and extrapolation, and optimization methods, this book is an essential reference source for decision makers, academicians, researchers, advanced-level students, technology developers, and government officials interested in the implementation of probabilistic modeling in various business applications.

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 as