Quantitative Models For Supply Chain Management

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.

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 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.

​​​​​​​Supply chain management (SCM) strives for creating competitive advantage and value for customers by integrating business processes from end users through original suppliers. However, the question of how SCM influences the value of a firm is not fully answered. Various conceptual frameworks that explain the coherence of SCM and company value, comprehended as value-based SCM, are well accepted in scientific research, but quantitative approaches to value-based SCM are found rather seldom. The book contributes to this research gap by proposing quantitative models that allow for assessing influences of SCM on the value of a firm. Opposed to existing models that limit the observation to chosen facets of SCM or selected value drivers, this holistic approach is adequate to • reflect configurational and operational aspects of SCM, • cover all phases of the product life cycle, • financially compare value impacts of profitability-related and asset-related value drivers, and • assess influences of dynamics and uncertainties on company value.​

Economic, marketing, and legislative considerations are increasingly leading companies to take back and recover their products after use. From a logistics perspective, these initiatives give rise to new goods flows from the user back to the producer. The management of these goods flows opposite to the traditional supply chain flows is addressed in the recently emerged field of Reverse Logistics. This monograph considers quantitative models that support decision making in Reverse Logistics. To this end, several recent case studies are reviewed. Moreover, first hand insight from a study on used electronic equipment is reported on. On this basis, logistics issues arising in the management of "reverse" goods flows are identified. Moreover, differences between Reverse Logistics and more traditional logistics contexts are highlighted. Finally, attention is paid to capturing the characteristics of Reverse Logistics in appropriate quantitative models.

This book addresses decision making in reverse logistics, which concerns the integration of used and obsolete products back into the supply chain as valuable resources. It covers a wide range of aspects, related to distribution, production and inventory management, and supply chain management. For each topic, it highlights key managerial issues in real-life examples and explains which quantitative models are available for addressing them. By treating a broad range of issues in a unified way, the book offers the reader a comprehensive view on the field of reverse logistics.

The Handbook is a comprehensive research reference that is essential for anyone interested in conducting research in supply chain. Unique features include: -A focus on the intersection of quantitative supply chain analysis and E-Business, -Unlike other edited volumes in the supply chain area, this is a handbook rather than a collection of research papers. Each chapter was written by one or more leading researchers in the area. These authors were invited on the basis of their scholarly expertise and unique insights in a particular sub-area, -As much attention is given to looking back as to looking forward. Most chapters discuss at length future research needs and research directions from both theoretical and practical perspectives, -Most chapters describe in detail the quantitative models used for analysis and the theoretical underpinnings; many examples and case studies are provided to demonstrate how the models and the theoretical insights are relevant to real situations, -Coverage of most state-of-the-art business practices in supply chain management.

This new edition focuses on three crucial areas of retail supply chain management: (1) empirical studies of retail supply chain practices, (2) assortment and inventory planning and (3) integrating price optimization into retail supply chain decisions. The book has been fully updated, expanding on the distinguishing features of the original, while offering three new chapters on recent topics which reflect areas of great interest and relevance to the academic and professional communities alike - inventory management in the presence of data inaccuracies, retail workforce management, and fast fashion retail strategies. The innovations, lessons for practice, and new technological solutions for managing retail supply chains are important not just in retailing, but offer crucial insights and strategies for the ultimate effective management of supply chains in other industries as well. The retail industry has emerged as a fascinating choice for researchers in the field of supply chain management. It presents a vast array of stimulating challenges that have long provided the context of much of the research in the area of operations research and inventory management. However, in recent years, advances in computing capabilities and information technologies, hyper-competition in the retail industry, emergence of multiple retail formats and distribution channels, an ever increasing trend towards a globally dispersed retail network, and a better understanding of the importance of collaboration in the extended supply chain have led to a surge in academic research on topics in retail supply chain management. Many supply chain innovations (e.g., vendor managed inventory) were first conceived and successfully validated in this industry, and have since been adopted in others. Conversely, many retailers have been quick to adopt cutting edge practices that first originated in other industries. Retail Supply Chain Management: Quantitative Models and Empirical Studies, 2nd Ed. is an attempt to summarize the state of the art in this research, as well as offer a perspective on what new applications may lie ahead.