Quantitative Planning and Control: Essays in Honor of William Wager Cooper on the Occasion of His 65th Birthday features a collection of papers prepared by students and associates of William Wager Cooper to honor him on the occasion of his sixty-fifth birthday. The book centers on the theme of Quantitative Planning and Control, the theme to which much of Professor Cooper's research effort has been devoted. The theme covers diverse fields of inquiry as reflected in the articles in this book, which are organized in four parts: (1) mathematical programming and decision models; (2) economic development and firm growth; (3) manpower planning and design; and (4) accounting and control. At the core of all of the articles in this book lies a belief that analytical approaches can help solve all managerial problems, a philosophy that is deeply rooted in Professor Cooper's thinking. This book demonstrates how this fundamental view on management can be reflected in dealing with problems in various fields of management. In particular, the book focuses on three main areas of application of this view, economic development, manpower planning, and accounting and control, along with the subject of developing tools that are necessary for solving managerial problems analytically.

This book focuses on the use of quantitative methods for both business and management, helping readers understand the most relevant quantitative methods for managerial decision-making. Pursuing a highly practical approach, the book reduces the theoretical information to a minimum, so as to give full prominence to the analysis of real business problems. Each chapter includes a brief theoretical explanation, followed by a real-life managerial case that needs to be solved, which is accompanied by a corresponding Microsoft Excel® dataset. The practical cases and exercises are solved using Excel, and for each problem, the authors provide an Excel file with the complete solution and corresponding calculations, which can be downloaded easily from the book’s website. Further, in an appendix, readers can find solutions to the same problems, but using the R statistical language. The book represents a valuable reference guide for postgraduate, MBA and executive education students, as it offers a hands-on, practical approach to learning quantitative methods in a managerial context. It will also be of interest to managers looking for a practical and straightforward way to learn about quantitative methods and improve their decision-making processes.

Singh introduces valuable techniques for weighing and evaluating alternatives in decision making with a focus on risk analysis for identifying, quantifying, and mitigating risks associated with construction projects.

Quantitative Methods in Supply Chain Management presents some of the most important methods and tools available for modeling and solving problems arising in the context of supply chain management. In the context of this book, “solving problems” usually means designing efficient algorithms for obtaining high-quality solutions. The first chapter is an extensive optimization review covering continuous unconstrained and constrained linear and nonlinear optimization algorithms, as well as dynamic programming and discrete optimization exact methods and heuristics. The second chapter presents time-series forecasting methods together with prediction market techniques for demand forecasting of new products and services. The third chapter details models and algorithms for planning and scheduling with an emphasis on production planning and personnel scheduling. The fourth chapter presents deterministic and stochastic models for inventory control with a detailed analysis on periodic review systems and algorithmic development for optimal control of such systems. The fifth chapter discusses models and algorithms for location/allocation problems arising in supply chain management, and transportation problems arising in distribution management in particular, such as the vehicle routing problem and others. The sixth and final chapter presents a short list of new trends in supply chain management with a discussion of the related challenges that each new trend might bring along in the immediate to near future. Overall, Quantitative Methods in Supply Chain Management may be of particular interest to students and researchers in the fields of supply chain management, operations management, operations research, industrial engineering, and computer science.

The thoroughly revised and updated book, now in its second edition, continues to present a comprehensive view of the concepts and applications of various quantitative models used in the study of operations and supply chain management. It provides a complete account of location and layout models, production planning models, production control models, cycle inventory models, safety stock models and transportation models. A separate chapter on real-life situations provides the user with the knowledge of specific areas where the models have been applied in decision-making processes. The various techniques to solve operations and supply chain management problems are also discussed. The text is supported by a large number of illustrative examples, exercises and review questions to reinforce the students’ understanding of the subject matter. Designed as a textbook for the students of mechanical and industrial engineering, the book would also be useful to postgraduate students of management. NEW TO THE SECOND EDITION • Two new chapters on ‘Production Control—Additional Approaches’ (Chapter 6) and ‘Materials Planning and Lot Sizing’ (Chapter 8) • Forecasting and Aggregate Planning are described in two separate chapters • Each chapter includes new sections, additional examples, illustrations, short questions and exercises • Provides solutions to the exercises

Quantitative models and computer-based tools are essential for making decisions in today's business environment. These tools are of particular importance in the rapidly growing area of supply chain management. This volume is a unified effort to provide a systematic summary of the large variety of new issues being considered, the new set of models being developed, the new techniques for analysis, and the computational methods that have become available recently. The volume's objective is to provide a self-contained, sophisticated research summary - a snapshot at this point of time - in the area of Quantitative Models for Supply Chain Management. While there are some multi-disciplinary aspects of supply chain management not covered here, the Editors and their contributors have captured many important developments in this rapidly expanding field. The 26 chapters can be divided into six categories. Basic Concepts and Technical Material (Chapters 1-6). The chapters in this category focus on introducing basic concepts, providing mathematical background and validating algorithmic tools to solve operational problems in supply chains. Supply Contracts (Chapters 7-10). In this category, the primary focus is on design and evaluation of supply contracts between independent agents in the supply chain. Value of Information (Chapters 11-13). The chapters in this category explicitly model the effect of information on decision-making and on supply chain performance. Managing Product Variety (Chapters 16-19). The chapters in this category analyze the effects of product variety and the different strategies to manage it. International Operations (Chapters 20-22). The three chapters in this category provide an overview of research in the emerging area of International Operations. Conceptual Issues and New Challenges (Chapters 23-27). These chapters outline a variety of frameworks that can be explored and used in future research efforts. This volume can serve as a graduate text, as a reference for researchers and as a guide for further development of this field.

Electronic Inspection Copy available for instructors here A must-have reference resource for quantitative management researchers, the Dictionary contains over 100 entries covering the fundamentals of quantitative methodologies; covering both analysis and implementation and examples of use, as well as detailed graphics to aid understanding. Every entry features: -An introduction to the topic, -Key relevant features, -A worked example, -A concise summary and a selection of further reading suggestions -Cross-references to associated concepts within the dictionary

An accessible introduction to the essential quantitative methods for making valuable business decisions Quantitative methods-research techniques used to analyze quantitative data-enable professionals to organize and understand numbers and, in turn, to make good decisions. Quantitative Methods: An Introduction for Business Management presents the application of quantitative mathematical modeling to decision making in a business management context and emphasizes not only the role of data in drawing conclusions, but also the pitfalls of undiscerning reliance of software packages that implement standard statistical procedures. With hands-on applications and explanations that are accessible to readers at various levels, the book successfully outlines the necessary tools to make smart and successful business decisions. Progressing from beginner to more advanced material at an easy-to-follow pace, the author utilizes motivating examples throughout to aid readers interested in decision making and also provides critical remarks, intuitive traps, and counterexamples when appropriate. The book begins with a discussion of motivations and foundations related to the topic, with introductory presentations of concepts from calculus to linear algebra. Next, the core ideas of quantitative methods are presented in chapters that explore introductory topics in probability, descriptive and inferential statistics, linear regression, and a discussion of time series that includes both classical topics and more challenging models. The author also discusses linear programming models and decision making under risk as well as less standard topics in the field such as game theory and Bayesian statistics. Finally, the book concludes with a focus on selected tools from multivariate statistics, including advanced regression models and data reduction methods such as principal component analysis, factor analysis, and cluster analysis. The book promotes the importance of an analytical approach, particularly when dealing with a complex system where multiple individuals are involved and have conflicting incentives. A related website features Microsoft Excel® workbooks and MATLAB® scripts to illustrate concepts as well as additional exercises with solutions. Quantitative Methods is an excellent book for courses on the topic at the graduate level. The book also serves as an authoritative reference and self-study guide for financial and business professionals, as well as readers looking to reinforce their analytical skills.

State of the art risk management techniques and practices—supplemented with interactive analytics All too often risk management books focus on risk measurement details without taking a broader view. Quantitative Risk Management delivers a synthesis of common sense management together with the cutting-edge tools of modern theory. This book presents a road map for tactical and strategic decision making designed to control risk and capitalize on opportunities. Most provocatively it challenges the conventional wisdom that "risk management" is or ever should be delegated to a separate department. Good managers have always known that managing risk is central to a financial firm and must be the responsibility of anyone who contributes to the profit of the firm. A guide to risk management for financial firms and managers in the post-crisis world, Quantitative Risk Management updates the techniques and tools used to measure and monitor risk. These are often mathematical and specialized, but the ideas are simple. The book starts with how we think about risk and uncertainty, then turns to a practical explanation of how risk is measured in today's complex financial markets. Covers everything from risk measures, probability, and regulatory issues to portfolio risk analytics and reporting Includes interactive graphs and computer code for portfolio risk and analytics Explains why tactical and strategic decisions must be made at every level of the firm and portfolio Providing the models, tools, and techniques firms need to build the best risk management practices, Quantitative Risk Management is an essential volume from an experienced manager and quantitative analyst.