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Author: Yuhe Diao Publisher: ISBN: Category : Heuristic Languages : en Pages : 61
Book Description
We study a single-item, multi-period, stochastic perishable inventory problem under both backlogging and lost-sales circumstances, with and without an order capacity constraint in each period. We first model the problem as a dynamic program and then develop two heuristics namely, Dual-Balancing (DB) and Look-Ahead (LA) policies, to approximate the optimal inventory level at the beginning of each period. To characterize the holding and backlog cost functions under the proposed polices, we introduce a truncated marginal holding cost for the marginal cost accounting scheme. Our numerical examples demonstrate that both DB and LA policies have a possible worst-case performance guarantee of two in perishable inventory systems under different assumptions, and the LA policy significantly outperforms the DB policy in most situations. We also analyze the target inventory level in each period (the inventory level at the beginning of each period) under different policies. We observe that the target inventory level under the LA policy is not larger than the optimal one in each period in systems without an order capacity constraint.
Author: Yuhe Diao Publisher: ISBN: Category : Heuristic Languages : en Pages : 61
Book Description
We study a single-item, multi-period, stochastic perishable inventory problem under both backlogging and lost-sales circumstances, with and without an order capacity constraint in each period. We first model the problem as a dynamic program and then develop two heuristics namely, Dual-Balancing (DB) and Look-Ahead (LA) policies, to approximate the optimal inventory level at the beginning of each period. To characterize the holding and backlog cost functions under the proposed polices, we introduce a truncated marginal holding cost for the marginal cost accounting scheme. Our numerical examples demonstrate that both DB and LA policies have a possible worst-case performance guarantee of two in perishable inventory systems under different assumptions, and the LA policy significantly outperforms the DB policy in most situations. We also analyze the target inventory level in each period (the inventory level at the beginning of each period) under different policies. We observe that the target inventory level under the LA policy is not larger than the optimal one in each period in systems without an order capacity constraint.
Author: Steven Nahmias Publisher: Springer Science & Business Media ISBN: 1441979999 Category : Business & Economics Languages : en Pages : 89
Book Description
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.
Author: Hossein Abouee Mehrizi Publisher: ISBN: Category : Languages : en Pages : 42
Book Description
In this paper, we study a multi-period stochastic perishable inventory system with multiple demand classes that require products of different ages. The firm orders the product with a positive leadtime and sells it to multiple demand classes, each only accepting products with remaining lifetime longer than a threshold. In each period, after demand realization, the firm decides how to allocate the on-hand inventory to different demand classes with different backorder or lost-sale cost. At the end of each period, the firm can dispose inventory of any age. We formulate this problem as a Markov decision process and characterize the optimal ordering, allocation, and disposal policies. When unfulfilled demand is backlogged, we show that the optimal order quantity is decreasing in the inventory levels and is more sensitive to the inventory level of fresher products, the optimal allocation policy is a sequential rationing policy, and the optimal disposal policy is characterized by a set of thresholds. For the lost-sale case, we show that the optimal allocation and disposal policies have the same structure but the optimal ordering policy may be different. Based on the structure of the optimal policy, we develop an efficient heuristic that is at most 4% away from the optimal cost in our numerical examples. Using numerical studies, we show that the ordering and allocation policies are close to optimal even if the firm cannot intentionally dispose products. Moreover, ignoring the difference between demand classes and using a simple allocation policy (e.g., FIFO) can significantly increase the total cost. We examine how the firm can improve the control of perishable items and show that the benefit of decreasing the leadtime is more significant than that of increasing the lifetime of the products or that of decreasing the acceptance threshold of the demand. The analysis is extended to systems with age dependent disposal cost and stochastic supply.
Author: Michael A. Völkel Publisher: Logos Verlag Berlin GmbH ISBN: 3832551077 Category : Mathematics Languages : en Pages : 119
Book Description
This book deals with inventory systems in supply chains that face risks that could render products unsalable. These risks include possible cooling system failures, transportation risks, packaging errors, handling errors, or natural quality deterioration over time like spoilage of food or blood products. Classical supply chain inventory models do not regard these risks. This thesis introduces novel cost models that consider these risks. It also analyzes how real-time tracking with RFID sensors and smart containers can contribute to decision making. To solve these cost models, this work presents new solution methods based on dynamic programming. In extensive computational studies both with experimental as well as real-life data from large players in the retailer industry, the solution methods prove to lead to substantially lower costs than existing solution methods and heuristics.
Author: Can Zhang Publisher: ISBN: Category : Languages : en Pages : 59
Book Description
Motivated by a platelet inventory management problem, we study periodic-review, fixed-lifetime perishable inventory systems where demand is a general stochastic process. The optimal solution for this problem is computationally intractable due to the “curse of dimensionality”. In this paper, we first present an approximation policy that we call the marginal-cost dual-balancing policy for perishable inventory systems. We prove that when first-in-first-out (FIFO) is an optimal issuing policy, our proposed policy admits a constant worst-case performance bound of two, a tighter performance bound compared to the existing results presented in the perishable inventory literature. We then extend the literature on the optimality of the FIFO issuing policy and present new sufficient conditions to ensure the optimality of FIFO. Further, we present a tight example to show that the performance bound of two of the balancing policy can be achieved asymptotically when the unit shortage penalty goes to infinity (in which case the balancing policy tends to under-order). Motivated by this result, we anticipate that the balancing policy as well as other existing balancing-type policies presented in the literature may perform poorly when the unit shortage penalty becomes large (these policies all tend to under-order), and we present a new policy that we call the truncated-balancing policy to overcome this shortcoming. By combining our worst-case analysis ideas for the balancing policy with a structural property called L-natural-convexity, we prove that the truncated-balancing policy also has a worst-case performance guarantee of two when FIFO is an optimal issuing policy. Finally, we conduct extensive numerical analyses and show that the truncated-balancing policy has a significant performance improvement over the existing policies when the unit shortage penalty becomes (reasonably) large.
Author: Stephen C. Graves Publisher: ISBN: Category : Inventory control Languages : en Pages : 25
Book Description
This paper develops three distinct models for studying perishable inventory systems. The perishable items have a deterministic usable life after which they must be outdated. For each of the models, analytical expressions are found for steady-state distributions which characterize the inventory systems. Knowledge of this steady-state behavior may be used for evaluation of system performance, and for consideration of alternatives for improving system performance. The first model considered assumes that both the demand process and the inventory replenishment process are stochastic processes that may be modelled as Poisson processes. The second and third model assume that inventory is replenished by a constant production process. The second model, assuming continuous inventory units, has Poisson demand requests with the size of each request distributed as an exponential random variable. The third model has Poisson demand requests with all demands being for a single unit. (Author).
Author: Evan L. Porteus Publisher: Stanford University Press ISBN: 9780804743990 Category : Business & Economics Languages : en Pages : 330
Book Description
This book has a dual purpose?serving as an advanced textbook designed to prepare doctoral students to do research on the mathematical foundations of inventory theory, and as a reference work for those already engaged in such research. All chapters conclude with exercises that either solidify or extend the concepts introduced.
Author: Anbazhagan, Neelamegam Publisher: IGI Global ISBN: 1522500456 Category : Business & Economics Languages : en Pages : 359
Book Description
Decision-making is an important task no matter the industry. Operations research, as a discipline, helps alleviate decision-making problems through the extraction of reliable information related to the task at hand in order to come to a viable solution. Integrating stochastic processes into operations research and management can further aid in the decision-making process for industrial and management problems. Stochastic Processes and Models in Operations Research emphasizes mathematical tools and equations relevant for solving complex problems within business and industrial settings. This research-based publication aims to assist scholars, researchers, operations managers, and graduate-level students by providing comprehensive exposure to the concepts, trends, and technologies relevant to stochastic process modeling to solve operations research problems.
Author: Yuhe Diao
Author: Yuhe Diao
Author: Steven Nahmias
Author: Hossein Abouee Mehrizi
Author: Michael A. Völkel
Author: Can Zhang
Author: Stephen C. Graves
Author: Bryan L. Deuermeyer
Author: Evan L. Porteus
Author: Sunjida Haque
Author: Anbazhagan, Neelamegam