Perishable Inventory Model Research Articles

Impact of inflation and discount on optimum ordering and preservation technology expenses scheme of perishable inventory model

This study coins an inventory model for deteriorating articles. The work devises an optimal approach of expenditure on preservation technology to attenuate the degradation process. The demand in the inventory model is both price and stock level sensitive. Demand in the form of price dependence is again a convex combination of linear and nonlinear prices. The investigation proliferates state-of-the-art strategy by presenting the concept of discount if payment is done in advance. The suggested model scrutinises the impact of inflation on optimality plan as well. The object of this exercise is to find optimal cycle length and preservation technology expenses to minimise the total cost per unit time. Stock is backlogged partially. Solution methodology of nonlinear minimisation problem embodies derivation of theorems and propositions. The final results are validated with the help of three examples, convexity of graphical schemes and sensitivity analysis. The paper also outlines the managerial point of view.

Impact of inflation and discount on optimum ordering and preservation technology expenses scheme of perishable inventory model

Impact of inflation and discount on optimum ordering and preservation technology expenses scheme of perishable inventory model

A Replenishment Inventory Model with a Stock-Dependent Demand and Age–Stock-Dependent Cost Functions in a Random Environment

This paper investigates an [Formula: see text] continuous-review perishable inventory model with a stock-dependent Poisson demand process, full backordering (with an extension for lost sales) and uncertainty in lead time and shelf life. Four types of costs are considered: a fixed cost of an order and each outdated item; age-dependent costs of an item (i.e., holding and salvage costs), given by a function of its remaining shelf life; and a delay cost of a backlogged demand unit, which is a function of its delay duration. Applying the supplementary variable technique, we obtain the joint probability-density function of the number of items in the system and the remaining time and thereby obtain the optimal parameters minimizing the long-run average total cost. Numerical experiments show that supply chain profits are enhanced by integrating the age components into replenishment decisions, and ignoring the shelf age- and delay-dependent costs may result in a substantial loss (up to 25%). It further appeared that estimating the lead-time distribution by an exponential one is significantly more costly, in particular as the c.v. differs from 1. In contrast, an exponential shelf life may provide a good heuristic for other shelf-life distributions.

Development of new hybrid discrete-time perishable inventory model based on Weibull distribution with time-varying demand using system dynamics approach

In the 20th century, there has been a significant development in logistics systems owing to market globalisation. From this perspective, our study focuses on designing novel models of inventory systems to reflect these real-time systems with improved accuracy and eventually design optimal control systems. Many mathematical inventory models lack details. Most of the existing models in the literature neglect the inclusion of closing days despite the shortening of the shelf-lifes of perishable items daily. In this study, a hybrid dynamic discrete-time inventory model with random lifetime perishable products, first in–first out (FIFO) and last in-first out (LIFO) issuing policies, positive lead time, and time-varying demand, including closing days, is developed. It is assumed that the demand is an external input to the model, and thus, it is easy to implement or test various market scenarios. The developed model is fitted to real data obtained from the research on the formation of botulinum toxin on packaged cubed melons and microbial spoilage at various incubation temperatures. Our study shows that the implementation of the Weibull distribution in modelling perishability can improve the accuracy of reflecting the performance of real physical inventory systems. We compare the developed model to an existing one in the literature, considering different issuing policies: FIFO, LIFO, and their combination. The study also includes a comparative analysis of the fixed and random lifetimes of products in terms of closing days.

A Joint Return Policy for a Multi-Item Perishable Inventory Model with Deterministic Demands, Return and All-Units Discount

In this paper, we develop a multi-item perishable inventory model with deterministic demands, return and all-units discount. We consider a situation where a retailer sells several products to the customer and orders the products from one supplier. Demands are assumed to be deterministic following an inventory-dependent demand, and the supplier offers all-units discount to the retailer who has an opportunity to return unsold or deteriorated products to the supplier at a certain cost. In order to minimize the total cost for the retailer, the decision variables are the optimal return time and the optimal ordering quantity. Considering a multi-item case as an extension of the model by Setiawan et al. (2018) is the main contribution of this paper. We also develop an algorithm to find the optimal solution of the model. Numerical examples for three items are given to illustrate the model and a sensitivity analysis is performed to study the effect of the changes in parameter values on the optimal solution. We consider two scenarios, one with all-units discount and one with no discount. Within these two scenarios, we consider conditions of individual or joint return time for these three items. It is found that the individual return time with no discount gives the least total inventory cost in the numerical examples. Also, in general increasing the value of holding cost, deteriorating rate, return cost per unit and backorder cost will increase the total inventory cost in all scenarios.

A discrete time perishable inventory model with positive lead time

A discrete time perishable inventory model with positive lead time

A two-phased perishable inventory model for production planning in a food industry

The food industry is faced with complicated inventory management problems because of the perishable nature of its raw materials, i.e., agricultural or marine products. Because agricultural and marine products spoil over time, it is necessary for inventory managers to employ a management strategy to prevent expiration of their storage periods. Furthermore, supply and demand of agricultural and marine products fluctuate considerably with climatic variations, seasonal changes and various social factors. Thus, a dynamic inventory model is to be devised concerning such fluctuation of supply and demand. In this paper, a two-phased perishable inventory model for a food industry is proposed, where the inventory is perishable, but can be renewed by additional processing. The proposed model is applied and demonstrated with a kimchi processing facility in Korea. Two heuristic solution methods for generating its inventory management plan are also presented along with computational experiments.

A Stochastic Inventory Model with Two Queues and a Flexible Server

This paper focusses on a perishable inventory model with two stations, namely, station 1 and station 2 with two dedicated servers and one flexible server, where service rates are different with respect to stations and servers. By using matrix analysis method, the joint stationary distribution of the number of customers in station 1 and station 2, the status of the servers and the inventory level under steady state are investigated. Some significant measures of the system performance are obtained. Finally, some intrinsic numerical examples are given.

Extended Abstract of Perishable Inventory Model for Postponed Demand with Reworks

Extended Abstract of Perishable Inventory Model for Postponed Demand with Reworks

Supply chain inventory model for perishable items under delayed payment

This paper attempts to create a supply chain inventory model for perishable goods that simultaneously considers delayed payment and shortage. For this purpose, a two-layer supply chain system was described, and a perishable goods inventory model was created for two types of grace periods. Then, the optimal distribution cycle and quantity were computed in the mode of single ordering and multiple distributions. Finally, the author investigated the effect of unit shortage cost, deterioration rate and grace period on the total cost of the supply chain. The model was validated through a case study. The research findings provide valuable references for inventory management of supply chain enterprises.

Development and simulation analysis of a new perishable inventory model with a closing days constraint under non-stationary stochastic demand

Abstract The food waste in grocery retail is a worldwide problem. Many mathematical inventory models for perishable items do not have a closing days constraint, although the age of perishable items also increases on closing days in grocery stores. We develop a new age-based inventory model with a closing days constraint. This stochastic multi-item inventory model includes total stock capacity constraints, a positive lead time, a periodic inventory control, a target customer service level and mixed FIFO and LIFO issuing policies for perishable items with a fixed lifetime under a non-stationary random demand. We show in a comparative simulation study under a rolling planning that the closing days constraint improves order decisions and reduces waste quantities and costs in grocery stores.

Perishable inventory model with Markovian arrival process, retrial demands and multiple working vacations

In this paper, we consider a continuous review perishable inventory system in which two types of customers, positive and negative, arrive according to a Markovian arrival process. The life time of an item and the lead time of reorder are exponentially distributed. Demands that occur during stock out period or busy period either enter an orbit of size N or are lost. The orbital demands compete their service with an exponential rate depending on the number of demands in the orbit. The waiting demands in the orbit may renege the system after an exponentially distributed amount of time. The server takes multiple working vacations at zero inventory. The steady state joint probability distribution of the number of customers in the orbit and the inventory level is obtained. Various performance measures and cost analysis are shown with numerical results.

Monitoring perishable inventory using quality status and predicting automatic devices under various stochastic environmental scenarios

Time-temperature-indicator (TTI)-based automatic devices (ADs) provide online information to incoming consumers regarding the expected shelf-life of products to be purchased. In this work, we extend the scope of simulation experiments conducted for solving a perishable inventory model, presented by the authors in previous work (Herbon et al., 2012). The model incorporates both dynamic pricing and TTI-based ADs for monitoring a perishable inventory system. The results have potential application in competitive markets such as the pharmaceutical and food industries. The current extension presents innovative results through the use of a random search algorithm combined with experimental design. Among the new scenarios explored in this study are different levels of the following: price-sensitivity; utility variability; expiry prediction error; demand variability; expected shelf-life; variability of shelf-life. It is found that the expected shelf-life and its variance significantly affect expected profits. Applying TTI-based ADs substantially mitigates the negative effect of the variability of shelf-life.

A retrial inventory system with priority customers and second optional service

In this paper, we investigate a single server (s, Q) perishable inventory model consisting of two priority customers, say, type-1 and type-2. The customers arrival flows are independent Poisson processes, and the service times of the type 1 and type 2 customers are exponentially distributed. The server offers two different types of services - first with ordinary service (essential service) and the second with optional service. The idle server first gives ordinary service to the arriving customers (type 1/type 2). Upon first essential service completion, then the server gives additional service (second optional) only to the type 1 customers. We assume that the type 1 customers have both types of priorities (non-preemptive priority and preemptive priority) over the type 2 customers. We discussed retrial concepts only for type-2 customers. The stationary probability distribution of the inventory level, status of the server, number of customer in the orbit and number of customers in the waiting line are obtained by matrix methods and some numerical illustrations are provided.

Perishable product inventory model based on the food supply chain

Food is the paramount necessity of the people. The food safety problem has been one of the issues of people's livelihood that the people and national focus on. Strengthening the food inventory management and improving the importance for the food safety of each enterprise and the government departments is an effective way to solve the food safety. In this paper, we study the inventory model of the perishable products. The stored time of the perishable products is short relatively. Therefore, how to carry out effectively the inventory model is an important step to improve the food safety degree. We study the inventory model of the perishable products. And we use the promotion to speed up the sale pace of the perishable products. Then it can reduce the food safety risks. According to the promotion of the perishable products, it not only can bring more profits for the business, but also can reduce the consumption of the perishable product, the bad motives of the businesses and improves the food safety level.

Perishable Inventory Model with Two Heterogeneous Servers Including One with Multiple Vacations and Retrial Customers

Perishable Inventory Model with Two Heterogeneous Servers Including One with Multiple Vacations and Retrial Customers

A perishable inventory model with two types of customers, Erlang-k service, linear repeated attempts and a finite populations

A perishable inventory model with two types of customers, Erlang-k service, linear repeated attempts and a finite populations

Limit Distribution of Inventory Level of Perishable Inventory Model

This paper studies a perishable inventory model, which assumes that each perishable item has finite lifetime, and only one item is consumed each time. The lifetimes of perishable items are independent random variables with the general distribution and so are the consumption internal. Under this assumption, by using backward equations and limit distribution of Markov skeleton processes, this paper obtains the existence conditions and the explicit expression of the limit distribution of the inventory level of perishable inventory model.

A perishable inventory model with Markovian renewal demands

In the inventory model, people usually assume that the inter-demand time is independently identical distributed which may not be true in reality. Here we study an ( s , S ) continuous review model for items with an exponential random lifetime and a general Markovian renewal demand process. By constructing Markovian renewal equations, we derive the mean and the variance of the reorder cycle time and lead to a simple expression for the total expected long run cost rate. The numerical results illustrate the system behavior and lead to managerial insights into controlling such inventory systems.

A perishable inventory model under stock-dependent selling rate and shortage-dependent partial backlogging with capacity constraint

This article develops a deterministic inventory model for perishable items with stock-dependent selling rate. In the model, the unsatisfied demand is partial backlogged and the backlogged demand rate is dependent on the negative inventory level during the stock-out period. Furthermore, a ceiling is imposed on the number of on-display stocks because too much inventory leaves a negative impression on the buyer and the amount of shelf space is limited. Next, the existence and uniqueness of the solution to the problem under two cases are examined, respectively. Then a solution procedure is shown to find the optimal replenishment policy of the considered problem. At last, two numerical examples and a real case study are presented to illustrate the application of the developed model.