Stochastic Perishable Inventory Systems: Dual-Balancing and Look-Ahead Approaches

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

A multi-criteria inventory management system for perishable & substitutable products

Perishable products represent a vital area in the retail industry and our daily lives. However, when considered with product substitution (which provides more choices) the short lifetime of perishable products creates significant challenges for the inventory management (e.g., one-third of food products are wasted). The main question is: what is the suitable ‘inventory policy’ when we have products that are both perishable and substitutable? Appropriate performance metrics are proposed to evaluate the whole system and provide a robust solution while also being easy for professionals to understand and adopt. Therefore, this paper proposes to use multi-metric approach, including Order Rate Variance Ratio, Average Inventory, and Fill Rate. The paper extends inventory theory to consider inventory management of products where they possess multi-period lifetime, positive lead time, required customer service level, and each item is treated separately. Under these circumstances, as the first research adopting these easily captured and analysed performance metrics, the proposed model will enable management of realistic scenarios by incorporating multiple inventory characteristics that support cross-functional continuous improvement

Inventory control for a non-stationary demand perishable product: comparing policies and solution methods

This paper summarizes our findings with respect to order policies for an inventory control problem for a perishable product with a maximum fixed shelf life in a periodic review system, where chance constraints play a role. A Stochastic Programming (SP) problem is presented which models a practical production planning problem over a finite horizon. Perishability, non-stationary demand, fixed ordering cost and a service level (chance) constraint make this problem complex. Inventory control handles this type of models with so-called order policies. We compare three different policies: a) production timing is fixed in advance combined with an order up-to level, b) production timing is fixed in advance and the production quantity takes the age distribution into account and c) the decision of the order quantity depends on the age-distribution of the items in stock. Several theoretical properties for the optimal solutions of the policies are presented. In this paper, four different solution approaches from earlier studies are used to derive parameter values for the order policies. For policy a), we use MILP approximations and alternatively the so-called Smoothed Monte Carlo method with sampled demand to optimize values. For policy b), we outline a sample based approach to determine the order quantities. The flexible policy c) is derived by SDP. All policies are compared on feasibility regarding the α-service level, computation time and ease of implementation to support management in the choice for an order policy.National project TIN2015-66680-C2-2-R, in part financed by the European Regional Development Fund (ERDF)

Effective sourcing strategies for perishable product supply chains

Purpose – The purpose of this paper is to assess whether an existing sourcing strategy can effectively supply products of appropriate quality with acceptable levels of product waste if applied to an international perishable product supply chain. The authors also analyse whether the effectiveness of this sourcing strategy can be improved by including costs for expected shelf life losses while generating order policies. Design/methodology/approach – The performance of sourcing strategies is examined in a prototype international strawberry supply chain. Appropriate order policies were determined using parameters both with and without costs for expected shelf life losses. Shelf life losses during transport and storage were predicted using microbiological growth models. The performance of the resulting policies was assessed using a hybrid discrete event chain simulation model that includes continuous quality decay. Findings – The study's findings reveal that the order policies obtained with standard cost parameters result in poor product quality and large amounts of product waste. Also, including costs for expected shelf life losses in sourcing strategies significantly reduces product waste and improves product quality, although transportation costs rise. Practical implications – The study shows that in perishable product supply chain design a trade-off should be made between transportation costs, shortage costs, inventory costs, product waste, and expected shelf life losses. Originality/value – By presenting a generically applicable methodology for perishable product supply chain design, the authors contribute to research and practice efforts to reduce food waste. Furthermore, product quality information is included in supply chain network design, a research area that is still in its infancy

Computing replenishment cycle policy parameters for a perishable item

In many industrial environments there is a significant class of problems for which the perishable nature of the inventory cannot be ignored in developing replenishment order plans. Food is the most salient example of a perishable inventory item. In this work, we consider the periodic-review, single-location, single-product production/inventory control problem under non-stationary stochastic demand and service level constraints. The product we consider can be held in stock for a limited amount of time after which it expires and it must be disposed of at a cost. In addition to wastage costs, our cost structure comprises fixed and unit variable ordering costs, and inventory holding costs. We propose an easy-to-implement replenishment cycle inventory control policy that yields at most 2N control parameters, where N is the number of periods in our planning horizon. We also show, on a simple numerical example, the improvement brought by this policy over two other simpler inventory control rules of common use

The Value of RFID Technology Enabled Information to Manage Perishables

We address the value of RFID technology enabled information to manage perishables in the context of a supplier that sells a random lifetime product subject to stochastic demand and lost sales. The product's lifetime is largely determined by the time and temperature history in the supply chain. We compare two information cases to a Base case in which the product's time and temperature history is unknown and therefore its shelf life is uncertain. In the first information case, the time and temperature history is known and therefore the remaining shelf life is also known at the time of receipt. The second information case builds on the first case such that the supplier now has visibility up the supply chain to know the remaining shelf life of inventory available for replenishment. We formulate these three different cases as Markov decision processes, introduce well performing heuristics of more practical relevance, and evaluate the value of information through an extensive simulation using representative, real world supply chain parameters.simulation;value of information;RFID;perishable inventory

A PERISHABLE INVENTORY MODEL WITH UNKNOWN TIME HORIZON

Traditionally, the time (planning) horizon over which the inventory for a particular item will be controlled is often assumed to be known (finite or infinite) and the total inventory cost is usually obtained by summing up the cost over the entire time horizon. However, in some inventory situations the period over which the inventory will be controlled are difficult to predict with certainty, as the inventory problems may not live up to or live beyond the assumed planning horizon, thereby affecting the optimality of the model. This paper presents a deterministic perishable inventory model for items with linear trend in demand and constant deterioration when time horizon is unknown, unspecified or unbounded. The heuristic model obtains replenishment policy by determining the ordering schedule to minimize the total cost per unit time over the duration of each schedule. A numerical example and sensitivity analysis are given to illustrate the model

An Inventory Model for Deteriorating Commodity under Stock Dependent Selling Rate

Economic order quantity (EOQ) is one of the most important inventory policy that have to be decided in managing an inventory system. The problem addressed in this paper concerns with the decision of the optimal replenishment time for ordering an EOQ to a supplier. This Model is captured the affect of stock dependent selling rate and varying price. We developed an inventory model under varying of demand-deterioration-price of commodity when the relationship of supplier-grocery-consumer at stochastic environment. The replenishment assumed instantaneous with zero lead time. The commodity will decay of quality according to the original condition with randomize characteristics. First, the model is addressed to solve a problem phenomenon how long is the optimum length of cycle time. Then, an EOQ of commodity to be ordered by will be determined by model. To solve this problem, the first step is developed a mathematical model based on reference’s model, and then solve the model analytically. Finally, an inventory model for deteriorating commodity under stock dependent selling rate and considering selling price was derived by this research. Keywords: deterioration commodity, expected profit, optimal replenishment time stock dependent selling rate