Books
Linear Programming
By George B. Dantzig and Mukund N. Thapa
Linear programming represents one of the major applications of mathematics to business, industry and economics. It provides a methodology for optimizing an output given that it is a linear function of a number of inputs. George Dantzig is widely regarded as the founder of the subject with his invention of the simplex algorithm in the 1940s.
This second volume is intended to add to the theory of the items discussed in the first volume. It also includes additional advanced topics such as variants of the simplex method, interior point methods (early and current methods), GUB, decomposition, integer programming and game theory. Graduate students in the fields of operations research, industrial engineering and applied mathematics will find this volume of particular interest.
Published by Springer-Verlag.
Managing the Supply Chain:
The Definitive Guide for the Business Professional
By David Simchi-Levi, Philip Kaminsky and Edith Simchi-Levi
In today's environment of tight budgets and even tighter turnarounds, effective supply-chain management has become a core business requirement. "Managing the Supply Chain" adapts the No. 1 supply chain book on the college market to examine how professionals can consistently turn supply chain strategy into a competitive advantage.
This results-based book examines the experiences of today's most accomplished companies to demonstrate supply chain innovation at work in the marketplace
Published by McGraw-Hill.
Supply Chain Management, Second Edition
By Sunil Chopra and Peter Meindl
This book has grown from a course on supply chain management taught to second-year MBA students at the Kellogg Graduate School of Management. The goal of this class is to cover not only high-level supply chain strategy and concepts, but also to give students a solid understanding of the analytical tools necessary to solve supply chain problems. With this class goal in mind, the authors' objective was to create a book that would develop an understanding of the following three key areas and their interrelationships: 1) the strategic role of the supply chain, 2) key drivers of supply chain performance, and 3) analytical tools and techniques for supply chain analysis.
The strategic framework and concepts discussed in the book are tied together through a variety of examples that show how a combination of concepts is needed to achieve significant increases in performance. There is a particular focus on the analysis of e-business and how it can help firms in different industries improve their supply chain performance.
Published by Prentice Hall.
Modeling the Supply Chain
By Jeremy F. Shapiro
With an emphasis on data, models and modeling systems, this text teaches professionals and students how to analyze supply chain planning problems. It overviews IT developments related to improving supply chain performance, introduces fundamentals of optimization modeling, explains design principles for supply chain network optimization systems, and presents a methodology for scheduling problems that combines optimization methods with heuristics. It also offers examples of modeling applications to strategic, tactical and operational supply chain planning problems.
The focus is on optimization models based on linear and mixed integer programming. Shapiro illustrates that when properly applied, these methodologies can create accurate and comprehensive models of great practical value. The book also shows how competitive advantage in supply chain management can be most fully realized by implementing and applying optimization modeling systems.
Published by Duxbury Press.
Marketing Logistics:
Customer Service & Supply Chain Strategy
By Martin Christopher, et al
This interface is being recognized by business organizations as a key priority for management, and both practitioners and academics alike have placed a greater emphasis on the need to view the supply chain as a whole as the vehicle by which competitive advantage is achieved.
As well as drawing upon current research and the experience of firms worldwide, "Marketing Logistics" uses numerous "mini-cases" and vignettes to illustrate the key messages in each chapter and bring the theory to life.
This book is a resource for managers who seek to understand more about the way in which the supply chain should be managed to improve their organization's competitive position, as well as students undertaking degree-level courses in marketing, logistics and supply chain management.
Published by Butterworth-Heinemann.
Introduction to Applied Optimization
By Urmila Diwekar
Most of the books in optimization are devoted to details of one or two aspect of the subject: they either focus on a particular methodology such as linear and nonlinear programming, stochastic programming, optimal control, stochastic dynamic programming, mixed integer programming, heuristic methods or multi-objective programming, or they are written for a specific discipline. The wide scope of optimization mandates extensive interaction between various disciplines in the development of the methods and algorithms, and in their fruitful application to real-world problems. This book presents a discipline-independent view of optimization for scientists, researchers and analysts in various fields. It provides them opportunities to identify and apply algorithms, methods and tools from the diverse areas of optimization to their own field without getting into too much detail about the underlying theories.
Published by Kluwer Academic Publishers.
Topics in Optimal Transportation
By Cedric Villani
This is the first comprehensive introduction to the theory of mass transportation with its many - and sometimes unexpected - applications. In a novel approach to the subject, the book both surveys the topic and includes a chapter of problems, making it a particularly useful graduate textbook.
In 1781, Gaspard Monge defined the problem of "optimal transportation" (or the transferring of mass with the least possible amount of work), with applications to engineering in mind. In 1942, Leonid Kantorovich applied the newborn machinery of linear programming to Monge's problem, with applications to economics in mind. In 1987, Yann Brenier used optimal transportation to prove a new projection theorem on the set of measure preserving maps, with applications to fluid mechanics in mind.
Each of these contributions marked the beginning of a whole mathematical theory, with many unexpected ramifications. Today, the Monge-Kantorovich problem is used and studied by researchers from extremely diverse horizons, including probability theory, functional analysis, isoperimetry, partial differential equations and even meteorology.
Published by the American Mathematical Society.
Operations Research in Space and Air
Edited by Tito A. Ciriani, Giorgio Fasano, Stefano Gliozzi and Roberto Tadei
The material within the book provides both the basic backgrounds for the novice modeler and a useful reference for experienced modelers. It represents the exploitation of recent mathematical tools and methods to solve large optimization models with contributions from leading-edge American and European companies and universities. Researchers and OR practitioners will appreciate the details of the modeling techniques, the processes that have been implemented and the computational results that demonstrate the benefits in applying OR in the space and airline industries.
Published by Kluwer Academic Publishers.
Operational Research in War and Peace: The British Experience from the 1930s to 1970
By Maurice W. Kirby
This is the first of two projected volumes on the history of operational research (OR) in Britain commissioned by the UK Operational Research Society. Based upon a vast array of published and unpublished sources, the book provides an original account of the discipline's pre-war and wartime origins. This serves as a prelude to a wide-ranging analysis of the diffusion of OR into the public and private sectors after 1945.
The chapters on the role of OR in iron and steel and coal mining, and its rapid adoption in the United Kingdom corporate sector after 1960, will be of particular interest to practitioners. The book also analyses and explains the diffusion of OR into local and central government and provides an informed commentary on the origins and subsequent history of the OR Society.
Professor Kirby has related the development of OR in the United Kingdom to contemporary developments in the United States. The book concludes with a resume of the post-1970 debates concerning the future trajectory of OR.
Published by World Scientific Publishing.
Applied Bayesian Modelling
By Peter Congdon
The use of Bayesian statistics has grown significantly in recent years, and will undoubtedly continue to do so. "Applied Bayesian Modelling" is the follow-up to the author's best-selling book, "Bayesian Statistical Modelling," and focuses on the potential applications of Bayesian techniques in a wide range of important topics in the social and health sciences. The applications are illustrated through many real-life examples and software implementation in WINBUGS - a popular software package that offers a simplified and flexible approach to statistical modeling. The book gives detailed explanations for each example, explaining fully the choice of model for each particular problem.
The book: provides a broad and comprehensive account of applied Bayesian modeling; describes a variety of model assessment methods and the flexibility of Bayesian prior specifications; covers many application areas, including panel data models, structural equation and other multivariate structure models, spatial analysis, survival analysis and epidemiology; and provides detailed worked examples in WINBUGS to illustrate the practical application of the techniques described.
Published by John Wiley & Sons.
Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning
By Abhijit Gosavi
This book introduces the evolving area of simulation-based optimization. Since it became possible to analyze random systems using computers, scientists and engineers have sought the means to optimize systems using simulation models. Only recently, however, has this objective had success in practice. Cutting-edge work in computational operations research, including non-linear programming (simultaneous perturbation), dynamic programming (reinforcement learning) and game theory (learning automata) has made it possible to use simulation in conjunction with optimization techniques. As a result, this research has given simulation added dimensions and power that it did not have in the recent past.
The book's objective is two-fold. First, it examines the mathematical governing principles of simulation-based optimization, thereby providing the reader with the ability to model relevant real-life problems using these techniques. Second, it outlines the computational technology underlying these methods. Taken together these two aspects demonstrate that the mathematical and computational methods discussed in this book do work.
Published by Kluwer Academic Publishers.
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