Inventory Policy Research Articles

EOI or EOQ? A simulation study for the inventory management of a company operating in the railway sector

The present paper proposes a study carried out in an Italian company operating in the railway industry, whose aim was to simulate two inventory management policies, namely the Economic Order Quantity (EOQ) and the Economic Order Interval (EOI) and compare the relating results from a set of simulations with historical data. The simulation was carried out on 53 articles (37 raw materials and 16 work in progress). The two models were developed under Microsoft Excel™, and their effectiveness was assessed in terms of amount of effective stock and the total costs associated; specifically, total costs are composed of three cost items: (i) order/production, (ii) stock keeping and (iii) stock out. Overall, both models returned better results in terms of economic saving and amount of stock than the current management policy used by the company; more specifically, the EOQ policy turned out to be the best, and was then selected for being implemented in the whole warehouse under investigation. Moreover, from a theoretical perspective, the need for a literature review on inventory management models emerged.

Multi-item EOQ model for deteriorating items having multivariate dependent demand with variable holding cost and trade credit

In the present study, a multi-item EOQ inventory model for deteriorating items is explored by considering customer's demand as a function of stock and selling price. Further, holding cost is considered as the function of stock-level and shortages are allowed, which partially backlogged. Further, trade credit policy is one of the attractive policies adopted by the supplier in the competitive market to boost the demand. Two different inventory models are investigated by considering the two situations, namely: a) the end stock level is negative; b) the end stock level is positive or zero. Different lemmas and theorems are provided to develop the search algorithm to obtain the optimal solution. The study shows the importance of multivariate demand and trade credit of the optimal policy of inventory. The feasibility of the proposed model is analysed with the help of a numerical example. Sensitivity is also carried out for critical parameters.

Supply chain coordination with flexible payment policy under effect of green technology investments

At present, augmentation of carbon gases in atmosphere has become a major concern. Regulatory bodies in many countries have focused on reduction of carbon emissions. Several countries follow carbon tax and carbon cap trade policy to control emission of carbon gases. This study has been carried out to obtain joint inventory policies for a supply chain involving a manufacturer and a whole-seller. Moreover, the manufacturer invests in green technology to reduce units of carbon gases. Products are considered deteriorating in nature. Manufacturer delivers product by adopting a lot-forlot policy to meet the whole-seller?s demand. The manufacturer offers the whole-seller flexible payment options including advance payment with discounted product price and delayed payment with increment in product price. Optimal policies for both individuals and the supply chain are discussed with aim to maximize total profit. The model is worked out and results are compared for four cases: (i) advance payment with green technology investments (ii) advance payment without green technology investments (iii) delayed payment with green technology investments (iv) delayed payment without green technology investments. A solution procedure has been proposed and explained through a numerical example. Study is concluded with managerial insights.

Implementation of inventory policy in local government units

Purpose: The aim of this article is to present the determinants of a properly conducted inventory process in local governments and to demonstrate the role of local Government Shared Service Centers (SSCs) in improving the quality of the inventory process. Design/methodology/approach: The authors, based on a research tool - a case study, presented the results of inventory conducted in a rural municipality using a selected municipality in the Kuyavian-Pomeranian Voivodeship as an example. The inventory process was preceded by an analysis and development of appropriate internal documents, as well as employee training. After the inventory was completed, surveys were conducted among the employees involved in this process. The collected responses and the conducted literature studies, especially the analysis of post-control findings of national control organizations such as the Regional Audit Offices, allowed for drawing conclusions and achieving the set research goal. Research limitations/implications: The conducted studies on the literature related to the subject and the available post-control findings in the area of public finances of local government units allow for drawing conclusions regarding the complexity of the inventory process. Despite the legally and substantively well-defined process of conducting inventory in the Accounting Act, public entities, and particularly the local government units examined in this article, still make many mistakes in this process. The inventory process is especially crucial for the accurate preparation of financial statements for entities, including local government units. Originality/value: The research highlights the need to distinguish between the organizational and substantive aspects of the inventory process. While local government units can handle the substantive part (selecting proper methods and principles for individual assets), the organizational aspect poses challenges, especially in rural municipalities with complex structures and limited staff. The study reveals the close connection between the inventory process and internal documents like Municipal Office Regulations, employee records, and asset responsibilities. The findings identify problematic areas in the inventory process. The authors suggest that utilizing SSCs could enhance efficiency and security. Keywords: inventory, Local Government Shared Services Centers, public finance, public management. Category of the paper: research paper.

Pricing strategy in an interval-valued production inventory model for high-tech products under demand disruption and price revision

Due to continuous development in technology, new and updated products are launching in the market more frequently in the area of some high-tech products such as smartphones, laptops, etc. It is noticed that after a certain period of releasing a new product by a particular company some other company develops a similar type of product at a lesser selling price. Customers generally become attracted to buy that updated product causing a sudden disruption in the demand for the first product. The demand for a normal product may also suddenly vanish as we have experienced during the COVID-19 lockdown period. The manufacturer is then compelled to reduce the selling price to sell the remaining products. This paper aims at developing a single period production inventory model addressing this particular market condition. This paper also considers carbon emissions from different inventory processes and examines the optimal inventory policies under the cap and trade regulatory policy. Again, in a real-life production system, the various inventory cost components and the carbon emission rates from different inventory processes are not fixed always. To incorporate this issue, the proposed model considers these quantities as interval numbers. The resulting optimization problem is thus also interval-valued and has been solved by using the quantum-behaved particle swarm optimization technique. A numerical illustration is provided to validate the proposed model. Finally, a sensitivity analysis with respect to key inventory parameters is performed to derive some key managerial implications. It is found that the frequency of launching new products is inversely proportional to the optimum profit of the manufacturer. Also, a higher carbon tax rate is found to be beneficial from an environmental point of view.

Optimal inventory policies for non-instantaneous deteriorating items with advance sales and advertisement efforts

Optimal inventory policies for non-instantaneous deteriorating items with advance sales and advertisement efforts

Inventory policy determination in MSMEs using intuitionistic fuzzy sets based on learning aided decision support system

Inventory policy determination in MSMEs using intuitionistic fuzzy sets based on learning aided decision support system

Developing trust among players in a vendor-managed inventory model for random demand under environmental impact.

Retailers play a vital role in supply chain management because they deal directly with consumers. Occasionally, retailers may cover the entire system's statistics and not disclose these data to the manufacturer. Therefore, asymmetry is generated in the data throughout the system. The main motive of this research was to prevent unreliability throughout the system using a vendor-managed inventory policy. This research shows that by applying a cap and trade policy, the total carbon emitted from the production and transportation sectors can be controlled in the atmosphere. Finally, numerical and sensitivity analyses, along with pictorial representations of various parameters, are performed to examine the optimal results of this study. In addition, the retailer's lead time demand for items is assumed to be random rather than fixed and follows uniform and normal distribution functions. Under these two distribution functions, the optimal retailer lot size, service provided by the retailer to customers, and retailer reorder points are assessed. Furthermore, an evaluation of the total carbon released from an environmental viewpoint is illustrated using numerical findings. The numerical results show that this research is 50.24% more economically beneficial than the methods used in previous studies, whereas the mean value of demand follows a uniform distribution.

A new procedure for spare parts inventory management in ETO production: a case study

Spare parts inventory management represents a strategic but critical process in many manufacturing companies, which have to handle a high amount of different items. This work aims at developing a simulation model to manage the inventory level of spare parts of an ETO (engineering to order) company. First, heterogeneous items have been analysed and classified into four different categories. Later, a simulation model has been developed to reproduce the inventory policy currently used to monitor and control them. Finally, a new procedure has been implemented to improve the current inventory management. Results show that the new procedure allows for reducing both the total cost and the maximum amount of space needed to stock the items. In addition, the simulation model could be used by practitioners as a practical tool to identify a proper inventory strategy according to the characteristics of the different items.

A Stochastic Integrated Inventory Model Single Supplier-Single Retailer in Periodic Review with Losing Flexibility Cost

Efficiency in the supply chain can be established by integrating the supplier-retailer inventory policy. This article proposes the integrated inventory model between supplier-retailer under stochastic demand. This model aims to determine the optimal review period and calculate the total inventory cost, including some defective items, backorder price discounts, and losing flexibility costs. We assume that the retailer can order 'n' times for every 'm' shipment from supplier to retailer in each production cycle under a periodic review. Stochastic conditions can cause sudden changes in orders by the retailer in large quantities, eventually forcing the supplier to reduce their setup policies. This condition makes the retailer be charged a losing flexibility cost as compensation for the reduction setup pushed by the supplier in a long-term partnership contract. Based on numerical examples and sensitivity analysis, the percentage of defective items in each shipment from supplier to retailer significantly affects integrated total inventory cost.

A Sustainable Production Recovery Model with Responsiveness in Demand and Quality Consideration during COVID-19 Crisis

The outbreak of the COVID-19 pandemic has resulted in severe economic consequences across the globe. Businesses have adopted various approaches to handle the stress of drastic changes in how businesses and consumers behave altogether. The decisions regarding inventory policies are greatly affected by the production rates and volumes, hence during this pandemic, flexibility in production rates and volumes becomes a necessity to handle demand uncertainties. Another big challenge that comes upfront is about rebuilding trust cum awareness in consumers about safe production, services, and home deliveries through constant investment in advertisements. To achieve supreme standards of quality, the manufacturers cannot afford any chance to compromise the quality of the product being delivered. Hence, the paper employs two-stage rigorous inspection practices for the imperfect products that arise from the production process, the first inspection process being error-prone (delivering Type- I and Type-II errors) while the second one being perfect. The developed model maximizes the manufacturer’s total profit by optimizing the investment in service and advertisement with a flexible production rate. A numerical example and comprehensive sensitivity analysis are illustrated to support the pragmatism of the model.

Inventory Sharing for Perishable Products: Application to Platelet Inventory Management in Hospital Blood Banks

A Simple and Provably Good Inventory Policy Led to a Significant Reduction in Platelet Outdates Platelets are critical blood products. The management of platelet inventory is particularly challenging because of its perishable nature with a short shelf life. This paper studies how the wastage of platelets and, more broadly, perishable products can be reduced through inventory sharing. The authors derive structural results on the optimal ordering and transshipment policies for a two-location perishable inventory system and prove that an easy-to-implement myopic transshipment policy is optimal for a few special cases relevant to practice and serves as a lower bound on the optimal transshipment policy for more general settings. This policy has been successfully implemented by the Emory University Hospital System, which led to a reduction of approximately 20% in platelet outdates. Moreover, this paper also sheds light on how the presence of inventory sharing affects the optimal ordering quantities and provides insights that significant depart from existing findings for nonperishable inventory systems.

Inventory management in the warehouse area of manufacturing companies. Literature Review, 2022

This literary review work, had as general objective to describe the context of inventory management in the manufacturing sector, this study was conducted by comparing articles published in indexed journals, in relation to inventory management, with inclusion criteria, such as English and Spanish language, with an age range of 4 years, ie from the year 2019 to the present, taking into account the pandemic conditions of a certain period. The sources that were analyzed within this work, were selected and placed within a table for their due classification both by objectives and results, in such a way to be able to find and make a comparison in reference to the context of inventory management.
 As a result, they were grouped into four groups where they are classified into "Decisions in COVID-19 times and the impact it had on the supply chain", "Systems applied for inventory management and resource utilization", "Methods applied to inventory management" and finally "Inventory policies and strategies", each group consisting of items.
 It was generally concluded that the impact obtained from COVID-19, within the supply chain, led organizations to reinvent new application strategies, thus increasing productivity and resource optimization.

Inventory information arrival and the crude oil futures market

AbstractThe objective of this paper is to provide a deeper insight into the impact of weekly inventory announcements and especially their associated surprises on crude oil returns and volatility during the period from 27 March 2012 to 2 October 2018. The results can be summarized as follows. First, we find that all inventory surprises exert an inverse impact on the oil price returns. Such impact appears more pronounced during the collapse and post‐collapse periods, than during the pre‐collapse period. Second, we show that the reducing volatility effects of inventory shocks that we establish for the whole period are entirely attributed to those observed in the pre‐collapse period. Third, the different effects obtained for positive and negative shocks support evidence that our split of inventory news by nature matters. Fourth, compared to macroeconomic and unconventional monetary news, the inventory statements appear as the most pertinent news during the event window. Fifth, we find evidence also that the effect of the uncertainty about economic stance, when it is significant, changes the way the oil prices and volatility react to inventory surprises, and hence weakens the effectiveness of the inventory policy. Lastly, we make an original use of the information content of the implied volatility to assess the persistence of the link between the conditional variance and the inventory news. The central finding is that the implied volatility enters with a significant effect on the conditional variance for WTI oil returns and namely with a reduced volatility persistence. Also, a significant effect from inventory surprises namely when we split the announcements into negative and positive news is detected even the implied volatility is introduced exogenously in the GARCH‐type variance specification highlighting the predominance of our main variable.

A Methodology for Clustering Items with Seasonal and Non-seasonal Demand Patterns for Inventory Management

Item clustering has become one of the most important topics in terms of effective inventory management in supply chains. Classification of items in terms of their features, sales or consumption volume and variation is a prerequisite to determine differentiated inventory policies as well as parameters, most common of which is service levels. Volume classification is easily obtained by well-known Pareto approach while coefficient of variance is usu-ally used for variation dimension. Hence, it is not always applicable to classify items under different product families with different demand patterns in terms of variation. In this paper, we propose two algorithms, one based on statistical analysis and the other an unsupervised machine learning algorithm using K-means clustering, both of which differ-entiate seasonal and non-seasonal products where an item’s variation is evaluated with respect to seasonality of the product group it belongs to. We then calculate the efficiency of two proposed approaches by standard deviation within each cluster and absolute difference of percentage of volume and item numbers. We also compare the outputs of two algorithms with the methodology which is based on coefficient of variance and is currently in use at the company which is a leading major domestic appliance manufacturer. The results show that the statistical method we propose generates superior outputs than the other two for both seasonal and non-seasonal demand patterns.

An optimal ordering inventory policy when the purchase price follows a discrete-time Markov chain

Most of the time retailers are offered discount prices that are occurring at random points in time. One such scenario is the supplier offering discounts to the retailers to increase market share, cash flow, and to reduce the inventory of specific items. Surprisingly no models exist in the literature survey to model the randomly occurring discount price under discrete time. The primary objective of this article is to develop an optimal inventory policy for a retailer when the discount price arrives randomly and the time variable is discrete. Under such a scenario, the optimal inventory policy can be obtained by considering the variations in the purchase price as a discrete-time Markov chain. The renewal reward theorem is used to derive the expected profit per unit of time. To illustrate the application of the developed model a real case study is considered. The optimal solution of the developed model is compared with the EOQ policy and found that the developed model solution provides better profit. This justifies the significance of the developed model. The inventory manager can use the developed model as a tool to obtain the optimal solution for any two price problems that repeat randomly.

Joint Optimization of Maintenance and Spare Parts Inventory for Multi-Unit Systems With a Generalized Structure

Abstract Joint optimization of maintenance operations and spare parts inventory is promising for ensuring the reliable and efficient operation of industrial systems. Extensive studies have been conducted on joint optimization emphasizing various aspects. However, those studies still suffer two limitations. (1) The considered system structures are restricted to particular cases, and thus are unable to fully address the joint optimization needs of actual industrial systems possessing various structures, and (2) imperfect maintenance, as has been commonly adopted in industries, is not addressed in existing works, which compromises the economic efficiency of the joint policy. Targeted at these limitations, this paper investigates the joint optimization for multi-unit systems with a generalized structure, i.e., the systems consist of multiple identical units, and each unit possesses a complex subsystem structure. First, a total cost rate model is formulated, in which maintenance actions include both perfect replacement and imperfect maintenance, and the spare parts inventory policy consists of an (s, S) policy and the option to place emergency orders. Based on the formulated model, a simulation optimization method is proposed. The simulation module evaluates the total cost rate iteratively, and the optimization module utilizes a variable neighborhood search-based algorithm to obtain a high-quality joint policy with tractable computation times. Two numerical examples are provided for demonstration, and sensitivity analyses are conducted to study the effects of parameters.

A deterministic model for the inventory policy of countries for procurement of vaccines.

The countries are the units that procure the vaccines during the COVID-19 pandemic. The delivered quantities are huge. The countries must bear the inventory holding cost according to the variation of stock quantities. This cost depends on the speed of the vaccination in the country. This speed is time-dependent. The vaccinated portion of the population can be approximated by the cumulative distribution function of the Cauchy distribution. A model is provided for determining the minimal-cost inventory policy and its optimality conditions are provided. The model is solved for 20 countries for different numbers of procurements. The results reveal the individual behavior of each country.

Impact of Ordering Decisions on Performance of a Supply Chain – An Experimental and Simulation Study

A supply chain consists of a network of organizations. Each organization in it acts as either customer or supplier to others. Ordering and replenishment decisions of each organization or stage contribute to supply chain performance. A simulation study and experimentation were conducted in this study to determine the impact of ordering decisions on supply chain performance. The ordering decisions at each stage are taken by intuition for experimentation and are taken by inventory policies for simulation. Under customer demand distribution information sharing, the performance of a supply chain is evaluated and compared between those two conditions. A supply chain role play game software package is used to evaluate supply chain performance by intuition, and simulation is used to evaluate different inventory policies. Fixed order policy, Order Up-to Level (OUL), Modified OUL (MOUL), (r, Q) and (r, S) inventory policies are considered in this study. The performance measures used are the total supply chain inventory per period, bullwhip effect and supply chain fill rate. Grey Relational Analysis (GRA) is used to identify the best method to take decisions in supply chain. Results show that supply chain performance is best under MOUL policy. Based on the results of this study, supply chain members are encouraged to identify the best inventory policy and use that rather than making decisions based on intuition.

Technical note on “Inventory management in supply chains with consideration of Logistics, green investment and different carbon emissions policies”

This study presents an extension of the model proposed by Huang et al. (2020), which investigated the effects of carbon policies and green technologies on the integrated inventory management of a two-echelon supply chain with consideration of carbon emissions during the processes of production, transportation, and storage. Specifically, since the inventory policy impacts on the economic and environmental performances of the supply chain, this study proposes a mathematical model for the integrated inventory management of the single-vendor single-buyer supply chain under a consignment stock policy. The aim is, thus, to highlight advantages and disadvantages of the consignment stock agreement with respect to the traditional policy based on the model proposed by Hill (1999). To compare the results, the same three carbon emissions policies are considered: i.e., limited total carbon emissions, carbon taxation, and cap-and-trade. The proposed model can assist firms in determining their optimal inventory policy (i.e., agreement, production quantity, delivery quantity, and green investment amount) with an aim of minimizing the supply chain costs under different carbon emissions policies.