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    One for one period policy for perishable inventory

    , Article Computers and Industrial Engineering ; Volume 79 , January , 2015 , Pages 10-17 ; 03608352 (ISSN) Mahmoodi, A ; Haji, A ; Haji, R ; Sharif University of Technology
    Elsevier Ltd  2015
    Abstract
    Recently, for zero ordering cost a new ordering policy named (1, T), in which the time interval between two consecutive orders and the value of the order size are both constant, have been developed for nonperishable products. In this paper, the (1, T) policy is developed for perishable products. Using an analogy among this inventory model, a queueing model with impatient customers, and a finite dam model, the long-run average total cost function of the inventory system is derived. It is observed that the total cost rate is independent from the lead time as is for nonperishable products. Since analyzing the convexity of the model is extremely complicated, a proposition is proved to define a... 

    An Inventory Model for Hospital Blood bank with the Objective of Minimizing Wastage and Shortage

    , M.Sc. Thesis Sharif University of Technology Eskandari, Hanieh (Author) ; Modarres Yazdi, Mohammad (Supervisor)
    Abstract
    In this research, among the levels of the blood supply chain, hospital is chosen for study because of its importance. A model of inventory management of hospital blood bank is presented. In this case, we consider some assumptions which are more realistic. These assumptions include two types of emergency and ordinary demands, young blood demand, and finally, a cross-match process. In the existing articles, although blood groups considered in mathematical models, the priority of allocation of blood groups is not considered in these articles. In this study, three mathematical models are developed with deterministic parameters. In the first model, the assumption of ordinary and emergency demand,... 

    An Application of Deep Reinforcement Learning in Novel Supply Chain Management Approaches for Inventory Control and Management of Perishable Supply Chain Network

    , M.Sc. Thesis Sharif University of Technology Mohammadi, Navid (Author) ; Akhavan Niaki, Taghi (Supervisor)
    Abstract
    This study proposes a deep reinforcement learning approach to solve a perishable inventory allocation problem in a two-echelon supply chain. The inventory allocation problem is studied considering the stochastic nature of demand and supply. The examined supply chain includes two retailers and one distribution center (DC) under a vendor-managed inventory (VMI) system. This research aims to minimize the wastages and shortages occurring at the retailer's sites in the examined supply chain. With regard to continuous action space in the considered inventory allocation problem, the Advantage Actor-Critic algorithm is implemented to solve the problem. Numerical experiments are implemented on...