This comprehensive Handbook provides an overview of state-of-the-art research on quantitative models for inventory management. Despite over half a century’s progress, inventory management remains a challenge, as evidenced by the recent Covid-19 pandemic. With an expanse of world-renowned inventory scholars from major international research universities, this Handbook explores key areas including mathematical modelling, the interplay of inventory decisions and other business decisions and the unique challenges posed to multiple industries.
This book develops a modeling framework to analyze the problem of inventory management with alternative delivery times. The general context considered here is that a seller replenishes its inventory in fixed intervals and, between replenishments, allocates the limited inventory to satisfy customers who are both price and delivery-time sensitive. On the demand side, customers have heterogeneous delivery-time requirements and choose either spot or late delivery. This theoretical modeling captures the essence of real-world business practices such as the delivery time market segmentation strategy adopted by automobile dealerships in China and many other similar examples. The book focuses on the seller’s optimal inventory replenishment and demand fulfillment policies, and our results provide managerial insights into the merits of flexible delivery-time options. Similar applications such as the group-buying mechanism are also examined. The main mathematical tool used in theoretical analysis is dynamic programming. This book is written for students, researchers, and practitioners in the areas of operations management and industrial engineering who are interested in understanding the rationale of flexible delivery times and designing successful applications.
Control and Dynamic Systems: Advances in Theory and Applications, Volume 46: Manufacturing and Automation Systems: Techniques and Technologies, Part 2 of 5 covers the significant advances and issues on the utilization of techniques and technologies in the manufacturing industries. This volume is divided into nine chapters and starts with the essential issue of software in manufacturing systems, particularly the aspects of the control software that are active in the time-critical or real time portions of the machine's operation. The succeeding chapters deal with the interactions between material-handling systems and other components of manufacturing systems; the principles of flexible manufacturing systems; the various views on the contributions of mechatronics; and the techniques for machine layout optimization in manufacturing and automation systems. These topics are followed by discussions of the application of a real-time control system to address issues of safety, productivity advances, and production cost reductions. Other chapters consider the influence of human supervisory control of predominantly automated manufacturing processes and the techniques for the manufacturing systems integration. The final chapter examines the major importance of the assembly line balancing to manufacturing systems. This book is of great value to process and mechanical engineers, as well as process control workers and researchers.
In the world of business management, most inventory models assume that open orders arrive after a lead time that cannot be controlled by the inventory manager. However, in many real world situations, inventory managers have the option to expedite open orders. Due to the lack of appropriate models, they often have to rely on sub-optimal heuristics to make expediting decisions. This book incorporates an expediting level policy in a periodic-review base-stock inventory model and shows how the optimal solution can be computed. The approaches can be implemented easily and are capable of solving large problems efficiently. While the book is mathematically rigorous, it presents important managerial insights gained from scenario analyses, using data from the service division of a global equipment manufacturer. (Series: Writings on Business Management Practice / Schriften zur betriebswirtschaftlichen Praxis - Vol. 7) [Subject: Business Management, Economics]
Here's an in-depth, step-by-step analysis defining the critical ingredients essential to achieving ongoing improvement and a robust bottom line! Focusing on practical, dynamic solutions for weaknesses in the interdependent parts of an organization, Management Dynamics provides a comprehensive introduction to the Theory of Constraints (TOC) in profit-oriented organizations, complete with the crucial but oft-missing pieces of the constraint theory–a fully integrated and supporting accounting system and the dynamic motivator to drive ongoing improvement in the bottom line. Order your copy today!
Many tasks in operations management require the solution of complex optimization problems. Problems in which decisions are taken sequentially over time can be modeled and solved by dynamic programming. Real-world dynamic programming problems, however, exhibit complexity that cannot be handled by conventional solution techniques. This complexity may stem from large state and solution spaces, huge sets of possible actions, non-convexities in the objective function, and uncertainty. In this book, three highly complex real-world problems from the domain of operations management are modeled and solved by newly developed solution techniques based on stochastic dynamic programming. First, the problem of optimally scheduling participating demand units in an energy transmission network is considered. These units are scheduled such that total cost of supplying demand for electric energy is minimized under uncertainty in demand and generation. Second, the integrated problem of investment in and optimal operations of a network of battery swap stations under uncertain demand and energy prices is modeled and solved. Third, the inventory control problem of a multi-channel retailer selling through independent sales channels is modeled and optimality conditions for replenishment policies of simple structure are proven. This book introduces efficient approximation techniques based on approximate dynamic programming (ADP) and extends existing proximal point algorithms to the stochastic case. The methods are applicable to a wide variety of dynamic programming problems of high dimension.
This handbook is an endeavour to cover many current, relevant, and essential topics related to decision sciences in a scientific manner. Using this handbook, graduate students, researchers, as well as practitioners from engineering, statistics, sociology, economics, etc. will find a new and refreshing paradigm shift as to how these topics can be put to use beneficially. Starting from the basics to advanced concepts, authors hope to make the readers well aware of the different theoretical and practical ideas, which are the focus of study in decision sciences nowadays. It includes an excellent bibliography/reference/journal list, information about a variety of datasets, illustrated pseudo-codes, and discussion of future trends in research. Covering topics ranging from optimization, networks and games, multi-objective optimization, inventory theory, statistical methods, artificial neural networks, times series analysis, simulation modeling, decision support system, data envelopment analysis, queueing theory, etc., this reference book is an attempt to make this area more meaningful for varied readers. Noteworthy features of this handbook are in-depth coverage of different topics, solved practical examples, unique datasets for a variety of examples in the areas of decision sciences, in-depth analysis of problems through colored charts, 3D diagrams, and discussions about software.
Inventory management aids businesses in determining which goods to order and when to order it. It keeps track of merchandise from purchase to sale. The practise monitors and reacts to trends to guarantee that there is always enough stock to satisfy client orders and that shortages are detected early. Inventory becomes revenue if it is sold. Inventory ties up cash before it sells, despite the fact that it is reported as an asset on the balance sheet. As a result, having too much inventory costs money and lowers cash flow. Inventory turnover is one indicator of good inventory management. Inventory turnover is an accounting metric that shows how frequently stock is sold over time. A company does not want to have more inventory than it can sell. Deadstock, or unsold inventory, can result from low inventory turnover. What Is the Importance of Inventory Management? Inventory management is critical to a business's success since it ensures that there is never too much or too little goods on hand, reducing the danger of stockouts and erroneous records. Inventory tracking is required by the Securities and Exchange Commission (SEC) and the Sarbanes-Oxley (SOX) Act for public corporations. To demonstrate compliance, businesses must document their management practises. Inventory Management's Advantages Inventory management has two key advantages: it assures that you can fulfil incoming or open orders and it increases earnings. Inventory control also entails: Saves Money: Knowing stock trends allows you to know how much and where you have anything in stock, allowing you to make better use of what you have. This also allows you to hold less stock at each location (store, warehouse), as you can fulfil orders from anywhere – all of this lowers inventory costs and reduces the quantity of product that goes unsold before it becomes obsolete. Improves Cash Flow: Proper inventory management allows you to spend money on inventory that sells, allowing cash to flow freely throughout the company. Customers are satisfied: ensuring that customers obtain the things they desire without having to wait is an important part of building loyal customers.
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