The integration of product recovery into regular production processes enables new opportunities for cost savings. In case of a dynamic planning situation, for instance when dealing with seasonality or the product life cycle, new motives for keeping stock arise. The work aims to identify those motives and to describe their effects by using methods of optimal control theory.
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.
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As markets become more dynamic and competitive, companies must reconsider how they view inventory and make changes to their production and inventory systems. They must begin to think outside the classical box and develop a new paradigm of inventory management. Exploring the trend away from classical models based on economic order quantities to depe
A perishable item is one that has constant utility up until an expiration date (which may be known or uncertain), at which point the utility drops to zero. This includes many types of packaged foods such as milk, cheese, processed meats, and canned goods. It also includes virtually all pharmaceuticals and photographic film, as well as whole blood supplies. This book is the first devoted solely to perishable inventory systems. The book’s ten chapters first cover the preliminaries of periodic review versus continuous review and look at a one-period newsvendor perishable inventory model. The author moves to the basic multiperiod dynamic model, and then considers the extensions of random lifetime, inclusion of a set-up cost, and multiproduct models of perishables. A chapter on continuous review models looks at one-for-one policies, models with zero lead time, optimal policies with positive lead time, and an alternative approach. Additional chapters present material on approximate order policies, inventory depletion management, and deterministic models, including the basic EOQ model with perishability and the dynamic deterministic model with perishability. Finally, chapters explore decaying inventories, queues with impatient customers, and blood bank inventory control. Anyone researching perishable inventory systems will find much to work with here. Practitioners and consultants will also now have a single well-referenced source of up-to-date information to work with.
The focus of the work is twofold. First, it provides an introduction into fundamental structural and behavioral aspects of periodic review inventory systems. Second, it includes a comprehensive study on analytical and optimization aspects of a specific class of those systems. For the latter purpose, general solution methods for problems of inventory management in discrete time are described and developed along with highly specialized methods to solve very specific problems related to the model variants examined. The work is thus addressed to students and practitioners who seek a deeper understanding of managing inventories in discrete time as well as to software developers who require implementation aids on specific problems of inventory management.
This volume contains revised and extended research articles written by prominent researchers participating in the conference. Topics covered include engineering physics, communications systems, control theory, automation, engineering mathematics, scientific computing, industrial engineering, and industrial applications. IAENG Transactions on Engineering Technologies: Special Issue of the International MultiConference of Engineers and Computer Scientists 2012 offers the state of art of tremendous advances in engineering technologies and physical science and applications, and also serves as an excellent reference work for researchers and graduate students working with/on engineering technologies and physical science and applications.
Optimal Control and Optimization of Stochastic Supply Chain Systems examines its subject the context of the presence of a variety of uncertainties. Numerous examples with intuitive illustrations and tables are provided, to demonstrate the structural characteristics of the optimal control policies in various stochastic supply chains and to show how to make use of these characteristics to construct easy-to-operate sub-optimal policies. In Part I, a general introduction to stochastic supply chain systems is provided. Analytical models for various stochastic supply chain systems are formulated and analysed in Part II. In Part III the structural knowledge of the optimal control policies obtained in Part II is utilized to construct easy-to-operate sub-optimal control policies for various stochastic supply chain systems accordingly. Finally, Part IV discusses the optimisation of threshold-type control policies and their robustness. A key feature of the book is its tying together of the complex analytical models produced by the requirements of operational practice, and the simple solutions needed for implementation. The analytical models and theoretical analysis propounded in this monograph will be of benefit to academic researchers and graduate students looking at logistics and supply chain management from standpoints in operations research or industrial, manufacturing, or control engineering. The practical tools and solutions and the qualitative insights into the ideas underlying functional supply chain systems will be of similar use to readers from more industrially-based backgrounds.
This volume provides a general overview of discrete- and continuous-time Markov control processes and stochastic games, along with a look at the range of applications of stochastic control and some of its recent theoretical developments. These topics include various aspects of dynamic programming, approximation algorithms, and infinite-dimensional linear programming. In all, the work comprises 18 carefully selected papers written by experts in their respective fields. Optimization, Control, and Applications of Stochastic Systems will be a valuable resource for all practitioners, researchers, and professionals in applied mathematics and operations research who work in the areas of stochastic control, mathematical finance, queueing theory, and inventory systems. It may also serve as a supplemental text for graduate courses in optimal control and dynamic games.
