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Статті в журналах з теми "Optimal inventory management"

Автор: Grafiati

Опубліковано: 30 травня 2022

Оновлено: 19 липня 2025

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Agrawal, Narendra, and Stephen A. Smith. "Optimal inventory management using retail prepacks." European Journal of Operational Research 274, no. 2 (2019): 531–44. http://dx.doi.org/10.1016/j.ejor.2018.10.014.

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Jakšič, M., and J. C. Fransoo. "Optimal inventory management with supply backordering." International Journal of Production Economics 159 (January 2015): 254–64. http://dx.doi.org/10.1016/j.ijpe.2014.09.015.

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Belousova, E. P. "OPTIMAL MANAGEMENT OF DISCRETE INVENTORY ALLOCATION." Region: systems, economy, management 58, no. 3 (2022): 147–53. http://dx.doi.org/10.22394/1997-4469-2022-58-3-147-153.

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Tayi, Giri Kumar. "Optimal inventory cycle counting." Omega 13, no. 6 (1985): 535–39. http://dx.doi.org/10.1016/0305-0483(85)90041-6.

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Baradel, Nicolas, Bruno Bouchard, David Evangelista, and Othmane Mounjid. "Optimal inventory management and order book modeling." ESAIM: Proceedings and Surveys 65 (2019): 145–81. http://dx.doi.org/10.1051/proc/201965145.

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We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [12, 18, 19], the MM and the HFT define their trading strategy by optimizing the expected utility of terminal wealth, while the IB has a prescheduled task to sell or buy many shares of the considered asset. We derive the variational partial differential equations that characterize the value functions of the MM and HFT and explain how almost optimal control can be deduced from them. We then provide a first illustration of the interactions that can take place between these different market participants by simulating the dynamic of an order book in which each of them plays his own (optimal) strategy.

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Su, Shou-Mei, and Shy-Der Lin. "The Optimal Inventory Policy of Production Management." Engineering 05, no. 05 (2013): 9–13. http://dx.doi.org/10.4236/eng.2013.55a002.

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Wagner, Michael R. "Robust Inventory Management: An Optimal Control Approach." Operations Research 66, no. 2 (2018): 426–47. http://dx.doi.org/10.1287/opre.2017.1669.

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Stoikova, L. S. "Optimal inventory management under incomplete demand information." Cybernetics and Systems Analysis 27, no. 4 (1992): 573–80. http://dx.doi.org/10.1007/bf01130369.

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Khetade, Khushi. "Intelligent Supply Chain Management." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48356.

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Анотація:

Fuzzy Logic is used to derive the optimal inventory policies in the Supply Chain (SC) numbers. We examine the per- formance of the optimal inventory policies by cutting the costs and increasing the supply chain management efficiency. The proposed inventory policy uses multi-agent and Fuzzy logic, and provides managerial insights on the impact of the decision making in all the SC numbers. In particular, we focus on the way in which our agent purchases components using a mixed procurement strategy (combining long and short term planning) and how it sets its prices according to the prevailing market conditions and its own inventory level (because this adaptivity and flexibility are key to its suc- cess). In modern global market, one of the most important issues of the supply chain (SC) management is to satisfy changing customer demands and enterprises should enhance the long-term advantage through the optimal inventory control. In this paper an intelligent multi-agent system to simulate supply chain management has been developed.

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Yu, Wenfang, Guisheng Hou, and Baogui Xin. "Decision-Making Optimization of Risk-Seeking Retailer Managed Inventory Model in a Water Supply Chain." Discrete Dynamics in Nature and Society 2021 (April 26, 2021): 1–18. http://dx.doi.org/10.1155/2021/9943753.

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Water retailer managed inventory is a classical and inevitable inventory management mode in present economic society. Stochastic models can more clearly explain demand uncertainty and are closely related to water supply chains. Risk preferences are widely valued in behavioral operation management. Related to the risk preferences in inventory management, the research on risk aversion is dominant, while risk-seeking is insufficient. Based on the model assumptions, the risk-seeking retailer’s optimal decision-making inventory model with stochastic demand in a water supply chain is studied. The risk-seeking retailer’s optimal inventory quantity, optimal inventory cost, supplier profit, retailer profit, and the profit of the entire water supply chain are derived. The validity of the equations is proved. The sensitivity analysis of the risk-seeking retailer’s optimal inventory decision-making is carried out. The risk level effects on the five dimensions, the retail price, wholesale price, unit shortage cost, unit inventory cost, and unit residual value, are displayed through numerical simulation. The optimal inventory quantity and optimal inventory cost of the risk-seeking retailer are obtained.

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Sun, Pei Hong, Lei Tang, and Li Ying Tang. "Application of Optimal Control in Inventory Management of Production." Applied Mechanics and Materials 29-32 (August 2010): 2503–8. http://dx.doi.org/10.4028/www.scientific.net/amm.29-32.2503.

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Анотація:

Countering the inventory management problem of manufacturing enterprise, according to the optimal control theory, considering the numbers of products as control variables and the stocks as the state variables, this essay establishes systemic real-time dynamic model, gives the objective function, and makes use of dynamic programming method to solve the optimal control and obtains the optimal inventory, which provides a theoretical foundation for the production and inventory management of manufacturing enterprise.

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Zhang, Mingyang, Xufeng Yang, Taichiu Edwin Cheng, and Chen Chang. "Inventory Management of Perishable Goods with Overconfident Retailers." Mathematics 10, no. 10 (2022): 1716. http://dx.doi.org/10.3390/math10101716.

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Анотація:

In recent years, many retailers sell their products through not only offline but also online platforms. The sales of perishable goods on e-commerce platforms recorded phenomenal growth in 2020. However, some retailers are overconfident and order more products than the optimal ordering quantity, resulting in great losses due to product decay. In this paper, we apply the newsvendor model to analyze the impacts of overconfident behavior on the retailer’s optimal pricing and order quantity decisions and profit. Our model provides the overconfident retailer with a feasible and effective method to adjust optimal ordering and pricing decisions. Through numerical studies, we examine the retailer’s optimal decisions under the scenarios of complete rationality, over-estimation, and over-precision. We find that the over-estimation retailer always orders more products than the optimal order quantity, and the over-precision retailer always orders fewer products than the optimal order quantity. Under some conditions, overconfidence hurts the retailer’s revenue to a large extent. Therefore, it is beneficial for the overconfident retailer to adjust its order quantity according to our research findings.

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Raviv, Tal, and Ofer Kolka. "Optimal inventory management of a bike-sharing station." IIE Transactions 45, no. 10 (2013): 1077–93. http://dx.doi.org/10.1080/0740817x.2013.770186.

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Usha, Pokhariya*and Prashant Mathur. "REVIEW ON: INVENTORY MANAGEMENT." Indo American Journal of Pharmaceutical Sciences 05, no. 04 (2018): 3124–31. https://doi.org/10.5281/zenodo.1236759.

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The pharmacy is one of the most extensively used facility in healthcare where a large amount of money is spent for purchasing medicinal items. In pharmacies, various drugs are being stored for supporting the therapy of patients. Due to the variety of pharmaceutical items, it is a difficult task to control and manage the quantity of drug. For a better and effective service management in a pharmacy, it is required a drug that must be provided continually at correct time and quantity to sustain steady in supply. This can be accomplished by efficient inventory management of pharmacy by providing control on important drugs, and deciding on priorities in purchase and distribution. Therefore, the inventory management is ensures significant improvement for both patient care and optimal use of resources. Three important methods regarding inventory management practice were studied such as ABC (Always, Better, Control) analysis, VED (Vital, Essential, Desirable) analysis, and ABC-VED matrix analysis. Keywords- Drug Inventory Management; Pharmacy; ABC; VED

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Calvert, Ian. "The Optimal Inventory Replenishment Review Period." Journal of the Operational Research Society 37, no. 3 (1986): 319. http://dx.doi.org/10.2307/2582213.

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Calvert, Ian. "The Optimal Inventory Replenishment Review Period." Journal of the Operational Research Society 37, no. 3 (1986): 319. http://dx.doi.org/10.1057/jors.1986.51.

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Gilabert, Horacio, and Marc E. McDill. "Optimizing Inventory and Yield Data Collection for Forest Management Planning." Forest Science 56, no. 6 (2010): 578–91. http://dx.doi.org/10.1093/forestscience/56.6.578.

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Abstract This work uses a Cost+Loss approach to estimate the optimal investment in inventory information for forest planning. A bootstrapping approach is used to simulate the impact of different inventory intensities on the quality of decisions in a linear programming harvest scheduling model. Multiple formulations of the harvest model based on varying inventory intensities are used to calculate the value of a variable labeled Loss that measures the monetary losses resulting from the use of imperfect yield information in the harvest model. The variable Loss and the cost of obtaining the inventory information are used to estimate empirical relationships between their expected value and the amount of inventory information (number of inventory plots and number of experimental plots) used in the harvest models. These two relationships are combined to give an explicit estimate of the expected Cost+Loss as a function of the inventory intensity variables. This Cost+Loss relationship is minimized to estimate optimal number of inventory plots and the optimal number of experimental plots. An example is developed with radiata pine information from southern Chile. Results for this example suggest that current practice uses too many experimental plots and too few inventory plots.

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I, Made Bagus Sindu Putra Dadri, and Ketut Purnawati Ni. "Inventory Management Analysis at UD Nuada Truss Tabanan Branch." International Journal of Social Science And Human Research 06, no. 08 (2023): 5223–28. https://doi.org/10.5281/zenodo.8291179.

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Анотація:

Inventory management must be considered by the company so that the inventory costs incurred do not burden the company too high and anticipate the occurrence of inventory shortages. This research was conducted at UD Nuada Truss Tabanan branch with the aim of knowing whether the performance of inventory management is optimal or not. This study uses descriptive analysis techniques using quantitative and qualitative data obtained from observations and interviews. This descriptive analysis technique will be explained in stages starting with ABC analysis, calculating EOQ, safety stock, reorder point, maximum inventory, inventory turnover, and total inventory cost. The results showed that the inventory management implemented by UD Nuada Truss Tabanan branch was not optimal. This is shown by the comparison of the total inventory cost incurred by the company's inventory management which is higher than the inventory management using the EOQ method. the total inventory cost incurred by the company's inventory management was IDR 69,074,629, while the inventory management using the EOQ method was IDR 53,038,890. The application of inventory management using the EOQ method provides efficiency to the company in the amount of IDR 16,035,739 (23.22%).

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ZHANG, JU-LIANG. "INTEGRATED DECISION ON PRICING, PROMOTION AND INVENTORY MANAGEMENT." Asia-Pacific Journal of Operational Research 29, no. 06 (2012): 1250038. http://dx.doi.org/10.1142/s0217595912500388.

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Firms often utilize promotion (such as coupons, advertisements, recruitment of excellent salespeople, and leafleting etc.) and dynamic adjustment of price to manage customers as well as proper production/inventory plan to satisfy the customers to get maximal profit in a firm. The decision on promotion and pricing and the decision on production/inventory must support each other. This paper addresses coordinated decision on pricing, promotion(non-price promotion) and inventory management. Specifically, we study a single item, periodic review model. The demand function is a linear demand function in which the market scale can be affected by the promotion conducted in that period. Unsatisfied demands are fully backlogged. We characterize the structure of the optimal policy that simultaneously determines the price, the promotion and the ordering quantity to maximize the total discounted profit with finite and infinite period problems. We show that the optimal replenishment policy is the quasi base stock list price target promotion policy, i.e., there exist a critical inventory level, a list price and a target promotion such that it is optimal to order up to the critical level, charge the list price and conduct the target promotion when the initial inventory is below the critical level and order nothing, conduct a higher promotion and charge a proper price to increase the demand otherwise. We also prove that the expected demand and the optimal promotion are increasing in the inventory, and price and promotion are complementary. Then we extend the problem to the case with capacity constraint. We show that the modified quasi base stock list price target promotion policy is optimal. For the joint decision problem on pricing, promotion and inventory control with positive fixed setup cost, we show that the optimal policy is (s, S, p, e) policy. That is, there exist two critical inventory levels stand St(st≤ St), a list price ptand a target promotion etin period t such that order up to St, charge price ptand conduct promotion etwhen the initial inventory is less than stand order nothing, charge a proper price and conduct a proper promotion otherwise.

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Szentesi, Szabolcs, and Gábor Nagy. "The Impact of Inventory Management Innovations on Industry 4.0 Manufacturing Strategies." Tehnički glasnik 19, Si1 (2025): 100–105. https://doi.org/10.31803/tg-20250410143130.

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In general, the goal of inventory management mechanisms is to develop inventory ordering rules that ensure optimal inventory levels. By "optimal inventory level," we mean a level where stock is always available when needed, while storage costs are minimized. To achieve this, a thorough understanding of inventory-related costs is essential for determining the economical level. In addition to classical and widely used inventory management mechanisms, many companies also employ mixed or hybrid inventory strategies, which are based on the combination of elements from different systems. In Industry 4.0 manufacturing, determining the inventory levels of raw materials and semi finished products presents a significant challenge for logistics professionals. Developments in Logistics 4.0, as well as advanced hybrid inventory management mechanisms, can provide substantial support to professionals in optimizing inventory levels.

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Yang, Jian, and Can Rong Zhang. "Study on the (s, S) Policy for the Manufacturing Enterprises Inventory Management." Advanced Materials Research 926-930 (May 2014): 3978–83. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3978.

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Using the inventory management in a manufacturing enterprise as the application background, this paper mainly studies on the optimal inventory policy for a part. The planning cycle of this problem is limited, and the demand in each planning cycle follows a discrete distribution. The objective is to minimize the inventory cost, namely, the total of transportation cost, inventory holding cost and penalty cost. Based on (s, S) policy, this paper puts forward two different inventory policies for the problem, and establishes two dynamic programming models accordingly. The numerical examples show that the optimal inventory policy significantly reduces the inventory cost.

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Kurniawan, Mohammad Fahmi, Sugiyono Madelan, and Ahmad Badawi Saluy. "Efficiency Analysis of Excavator Nut Inventory Using Economic Order Quantity Method at PT. ABCDE Bekasi-Jawa Barat." Dinasti International Journal of Economics, Finance & Accounting 2, no. 3 (2021): 295–305. http://dx.doi.org/10.38035/dijefa.v2i3.859.

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Inventory management is one of the keys to the success of the production process in any company, including manufacturing companies. Therefore, determining the optimal amount of inventory is crucial for inventory management. In a production process, sometimes a condition is found where the amount of inventory far exceeds what is needed, so that in the process of implementing the specifications change of an inventory will take quite a long time, this is due to an effort to use up obsolete inventory first, so it is necessary to calculate the optimal value of the company inventory. In this research, using the Economic Order Quantity and Reorder Point analysis method in the POM-QM software, it is expected to determine the optimal value of the purchase amount, Safety Stock, Reorder Point, and the required inventory costs of J950010 nuts. The results showed that although there were differences between the results of the POM-QM calculation and the application in the field, the management of J950010 nut stock is optimal.

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Wang, Yun Rui. "Enterprise Inventory Management and Simulation." Advanced Materials Research 933 (May 2014): 874–78. http://dx.doi.org/10.4028/www.scientific.net/amr.933.874.

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Inventory is an important link in supply chain, according to characteristics and objectives of inventory control, the reasonable safety inventory, order point, the highest inventory and inventory strategy were determined based on historical sales data. Using Witness simulation software, the optimal strategy was selected from nine inventory strategies by running simulation model for one year. If goods shortage was allowing, the seventh schemes (72000,158100) was better ,the minimum total cost was 888158 yuan ; considering allowing a small amount of shortage, the cost of eighth schemes ( 82000,158100) was least of 1095167; the third scenarios (92000,138100) was selected if without shortage, and the minimum total cost was 1254909 yuan. This shows, the application of computer simulation to assist in the management of inventory is scientific and feasible, it can help enterprises to save the order and operation cost.

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Tan, Nguyen Duy, Hwan-Seong Kim, Le Ngoc Bao Long, Duy Anh Nguyen, and Sam-Sang You. "Optimization and inventory management under stochastic demand using metaheuristic algorithm." PLOS ONE 19, no. 1 (2024): e0286433. http://dx.doi.org/10.1371/journal.pone.0286433.

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This study considers multi-period inventory systems for optimizing profit and storage space under stochastic demand. A nonlinear programming model based on random demand is proposed to simulate the inventory operation. The effective inventory management system is realized using a multi-objective grey wolf optimization (MOGWO) method, reducing storage space while maximizing profit. Numerical outcomes are used to confirm the efficacy of the optimal solutions. The numerical analysis and tests for multi-objective inventory optimization are performed in the four practical scenarios. The inventory model’s sensitivity analysis is performed to verify the optimal solutions further. Especially the proposed approach allows businesses to optimize profits while regulating the storage space required to operate in inventory management. The supply chain performance can be significantly enhanced using inventory management strategies and inventory management practices. Finally, the novel decision-making strategy can offer new insights into effectively managing digital supply chain networks against market volatility.

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Davison, Matthew, Yuri Lawryshyn, and Volodymyr Miklyukh. "Optimal inventory policy through dual sourcing." Computational Management Science 17, no. 2 (2020): 327–55. http://dx.doi.org/10.1007/s10287-020-00371-8.

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Dimitrov, Stanko, and Oben Ceryan. "Optimal inventory decisions when offering layaway." International Journal of Production Research 57, no. 4 (2018): 1161–75. http://dx.doi.org/10.1080/00207543.2018.1502484.

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Khmelnitsky, Eugene, and Gonen Singer. "An optimal inventory management problem with reputation-dependent demand." Annals of Operations Research 231, no. 1 (2014): 305–16. http://dx.doi.org/10.1007/s10479-014-1600-z.

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Aardal, Karen, Orjan Jonsson, and Henrik Jonsson. "Optimal Inventory Policies with Service-Level Constraints." Journal of the Operational Research Society 40, no. 1 (1989): 65. http://dx.doi.org/10.2307/2583078.

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Aardal, Karen, Örjan Jonsson, and Henrik Jönsson. "Optimal Inventory Policies with Service-Level Constraints." Journal of the Operational Research Society 40, no. 1 (1989): 65–73. http://dx.doi.org/10.1057/jors.1989.6.

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Assiddiqi, Muktadi Amri, Samuel Pd Anantadjaya, Israr Ahmad, et al. "Integrated Pricing and Inventory Control for Perishable Products, Taking into Account the Lack of Backlog and Inventory Management Policy by the Seller." Foundations of Computing and Decision Sciences 47, no. 4 (2022): 371–82. http://dx.doi.org/10.2478/fcds-2022-0020.

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Анотація:

Abstract Recently, utilizing appropriate inventory control policy and determining the optimal selling price for various goods has been the main topic of scientific and industrial research. Inventory management policy 1 by the seller is one solution that improves the chain’s performance by creating coordination between members of the supply chain. The current study attempts to devise an integrated model of inventory pricing and control under the inventory management policy by the seller for perishable goods with shortages is considered. The purpose of presenting the model is to determine the optimal price, the optimal repayment time, and the order size, in order to maximize the profit. To acquire those optimal values, the profit functions of the buyer and the seller are taken into account. Given the results acquired, it is demonstrated that at any cost, the repayment time is unique and optimal. It is concluded that with the optimal recovery time available, the objective function is a concave function of price, and its optimal value is available. Furthermore, utilizing the inventory management policy by the seller could be a proper means to reducing retailer costs while raising their profit.

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Goonatilake, Rohitha, and Sofia C. Maldonado. "Essentials of Novel Inventory Management Systems." Engineering Management Research 7, no. 1 (2018): 31. http://dx.doi.org/10.5539/emr.v7n1p31.

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Анотація:

Keeping inventories adequately maintained to meet the demands of future sales or uses in business enterprises determines the extent of business’s success. Hence, a successful inventory management is necessary, in particular, guided by the formulating of deterministic, stochastic, and probabilistic models. This essentially describes optimal inventory policies in terms of when and how to replenish the inventory. In this paper, we discuss several basic considerations used in determining inventory models that address the needs of current manufacturing and business enterprises. Theories and essentials supported by the novel approaches are integrated to reflect the representation of many actual situations. Multi-product and multi-facility models are given additional consideration at the end.

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Okpara, Godwin Chigozie, and Okuu Kalu Okwuagwu. "Inventory Management in Corporate Firms: Reasons for and Techniques." International Journal of Research and Innovation in Social Science IX, no. II (2025): 4249–58. https://doi.org/10.47772/ijriss.2025.9020332.

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Анотація:

This paper aims at explaining and exposing the importance of inventory management in a corporate firm. In this work, the exposition of inventory as stock of various kinds such as raw materials, work in progress, maintenance, repairs and operating goods, finished goods and safety stocks incited the question of how and ways the inventories could be managed to achieve the optimal quantity and required profitability for engendering sustainable growth of the firm. In a bid to obtaining the optimal quantity, various costs associated with the inventory and the techniques of optimizing the quantity and minimizing the costs for effective management were elucidated. Thus, if the elucidated techniques are appropriately and religiously adopted, efficient inventory management and hence sustainable growth of the firms will be assured.

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Vidiasari, Mike, and Ribangun Bamban Jakaria. "A Planning Purchasing Policies for Raw Material Welding Wire Using Economic Order Quantity (EOQ) Method to Reduce Overstock." Procedia of Engineering and Life Science 7 (February 21, 2024): 1–5. http://dx.doi.org/10.21070/pels.v7i0.1587.

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This study aims to determine the optimal order quantity of K71T welding wire for PT BMI's boiler production process to reduce storage and inventory costs. The Economic Order Quantity (EOQ) method is applied to calculate the optimal amount of material to be ordered in one period. The results show that the total inventory cost using the EOQ method is Rp. 89,060,000,- compared to the company policy of Rp. 290,840,000,-. The optimal number of orders is 407 boxes with a purchase frequency of 4 times per year and a safety stock of 181 boxes. The findings of this study can be used as a reference for other manufacturing companies that face similar procurement challenges to optimize their inventory management and reduce costs. Highlight :  The study determines the optimal order quantity of K71T welding wire, reducing storage and inventory costs. The Economic Order Quantity (EOQ) method is applied, resulting in a total inventory cost of Rp. 89,060,000,- compared to the company policy of Rp. 290,840,000,-. The findings can be used as a reference for other manufacturing companies facing similar procurement challenges to optimize their inventory management and reduce costs.  Keywords: welding wire, optimal order quantity, inventory management, procurement challenges, manufacturing companies

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Kukartsev, Vladislav, Anastasia Kozlova, Olga Kuimova, Vladimir Nelyub, and Andrei Gantimurov. "Using digital twins to create an inventory management system." E3S Web of Conferences 431 (2023): 05016. http://dx.doi.org/10.1051/e3sconf/202343105016.

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Анотація:

The article considers the application of the inventory management model on the example of a manufacturing enterprise, where it is planned to use a digital twin together with the inventory management system. Inventory management model is a mathematical model that allows you to determine the optimal level of stocks at the enterprise. In a manufacturing enterprise, this model can help optimize the inventory of raw materials, materials, and finished goods, which will reduce costs and reduce risks associated with the lack of necessary raw materials or required quantities of finished goods. With the help of data obtained from the enterprise, the input parameters of the model were obtained, namely the size of resource consumption, stock holding costs, delivery realization costs, and time required for delivery. The model was used to find the parameters such as optimal order size, delivery period, inventory level at which ordering should be carried out.

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Qiu, Yuzhuo, Jun Qiao, and Panos M. Pardalos. "Optimal production, replenishment, delivery, routing and inventory management policies for products with perishable inventory." Omega 82 (January 2019): 193–204. http://dx.doi.org/10.1016/j.omega.2018.01.006.

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Ruiz, Cesar, Edward Pohl, and Haitao Liao. "Bayesian degradation modelling for spare parts inventory management." IMA Journal of Management Mathematics 32, no. 1 (2020): 31–49. http://dx.doi.org/10.1093/imaman/dpaa008.

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Abstract Decision makers in various sectors, such as manufacturing and transportation, strive to minimize downtime costs. Often, brief-planned stoppage times allow for changes in shifts and line configurations and longer periods are scheduled for major repairs. It is quite important to proactively make use of these downtimes to reduce the costs of unexpected downtimes due to failures. Among many aspects, the availability of spare parts significantly affects the operational costs of such systems. Current sensor technologies enable the condition monitoring of critical components and degradation-based spare parts management. This paper focuses on Bayesian degradation modelling for spare parts inventory management for a new system. We propose a stochastic dynamic program to minimize the expected spare parts inventory cost for a fixed planning horizon. A numerical example illustrates the value of Bayesian analysis in this management setting. The proposed methodology finds the optimal time between long stoppages and optimal spare parts order quantity when the prior information about the degradation process is accurate. The methodology can be used to analyse the sensitivity of the optimal solution to changes in the accuracy and bias of the prior distributions of the model parameters, the cost structure and the number of machines in the system.

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Lutfiana, Lina. "ANALISIS MANAJEMEN PERSEDIAAN UMKM JAZID BASTOMI BATIK DI PURWOREJO." Jurnal Ekonomi Syariah, Akuntansi dan Perbankan (JESKaPe) 4, no. 1 (2020): 55–66. http://dx.doi.org/10.52490/jeskape.v4i1.689.

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Abstract This study aims to know more effective inventory management in UMKM Jazid Bastomi Batik. With descriptive qualitatif approach, researcher analyze inventory management done in UMKM Jazid Bastomi Batik. Observation and interview and documentation data results show inventory management of UMKM Jazid Bastomi Batik optimal yet. This is showing a minimum inventory, because limited inventory. For that, reseacher use safety stock technique, EOQ, and ROP to analyze inventory. It can improve effective and efficient inventory management. Keywords: Inventory, Inventory Management, Safety Stock, EOQ, ROP  Abstrak Studi ini bertujuan untuk mengetahui manajemen persediaan yang paling efektif pada UMKM Jazid Bastomi Batik. Dengan pendekatan kualitatif deskriptif, peneliti menganalisis manajemen persediaan di UMKM Jazid Bastomi Batik.Data hasil observasi wawancara, dan dokumentasi menunjukkan bahwa manajemen persediaan pada UMKM Jazid Bastomi Batik belum optimal. Hal ini ditunjukkan dengan minimnya persediaan yang ada, karena terdapat keterbatasan dalam mengelola persediaan. Untuk itu, peneliti menggunakan teknik safety stock, EOQ, dan ROP untuk menganalisis persediaan yang dapat menunjang pengelolaan persediaan secara efektif dan efisien. Kata kunci: Persediaan, Manajemen Persediaan, Safety Stock, EOQ, ROP

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Adelia, Anggun, Fani Iis Fitrianti, Gerhana Bulan Safitri, and Nanik Kustiningsih. "D. ANALISIS MANAJEMEN PERSEDIAAN PADA USAHA ANGGUN HIJAB." Inovasi Manajemen dan Kebijakan Publik 4, no. 2 (2021): 60. http://dx.doi.org/10.54980/imkp.v4i2.159.

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Abstrak Usaha Mikro, Kecil dan Menengah UMKM memiliki peran yang penting dalam perekonomian.. Studi ini bertujuan untuk menentukan manajemen inventory yang paling efektif pada UMKM Anggun Hijab. Metode yang kami gunakan adalah pendekatan kualitatif deskreptif dengan kegiatan wawancara dan observasi. Hasil riset menunjukkan bahwa manajemen inventory pada UMKM anggun hijab belum optimal. hal ini ditunjukan dengan minimnya persediaan yang ada, karena terdapat keterbatasan dalam mengelola. untuk itu, penelitu menggunakan teknik safety stock dan EOQ untuk menganalisis persediaan yang dapat menunjang pengelolaan persediaan secara efektif dan efisien. kata kunci : analisis manajemen persediaan  Abstract Micro, Small and Medium Enterprises UMKM have an important role in the economy. This study aims for the most effective inventory management in UMKM Anggun Hijab. with a descriptive qualitative approach, the researcher analyzed inventory management in UMKM Anggun Hijab. Inventory management constraints that occur in UMKM Anggun Hijab can be overcome by using the right system in inventory management. Data from interview observations show that inventory management at the Graceful Hijab UMKM is not optimal. this is indicated by the lack of existing inventory, because there are limitations in managing. For this reason, researchers use safety stock and EOQ techniques to analyze inventory that can support inventory management effectively and efficiently. Keywords: inventory management analysis

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Meena, Pooja, Sita Meena, Anil Kumar Sharma, and Ganesh Kumar. "INVENTORY MANAGEMENT IN INFLATIONARY ENVIRONMENT UNDER DELAY IN PAYMENTS WITH SHORTAGES." Jnanabha 51, no. 01 (2021): 159–71. http://dx.doi.org/10.58250/jnanabha.2021.51121.

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This paper, provides a replenishment strategy where demand rate is an algebraic function of time and selling price. The deterioration is taken constant over the ordering cycle time. Shortages are permitted and are partly backlogged. The aim of this model is to maximize the total profit under payment delays and inflation. An algorithm to determine the optimal selling price, optimal stockout length, optimal replenishment cycle time, and optimal closing inventory level is provided. Numerical examples, graphical representation, and sensitivity analysis are discussed to explain the proposed inventory model.

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Arovina, Maryna, and Volodymyr Suhoniak. "SELECTION OF AN INVENTORY MANAGEMENT MODEL FOR ROAD PAVEMENT PRODUCTION." Economic scope, no. 199 (April 14, 2025): 3–9. https://doi.org/10.30838/ep.199.3-9.

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The article is devoted to substantiating the choice of inventory management models for making effective decisions in the process of road pavement production. Based on a review of scientific papers, the advantages and disadvantages of common models are identified. The main factors, such as production recipe, storage conditions of raw materials, and demand for finished products, are considered. The peculiarities of their influence on inventory management in the field of road pavement production are determined, provided that there is no shortage of raw materials. A comparison of common deterministic inventory management models is carried out: ABC-analysis, Economic Optimal Quantity, Minimum-maximum, Just in Time, and others. The ABC analysis of the main components of the road pavement formulation is carried out. The ABC classification based on financial impact allowed us to identify the component of priority inventory control by concluding long-term contracts with suppliers and managing inventory on the Just in Time principle. The Economic Optimal Quantity model was used to perform calculations under two scenarios: a 12-month constant demand cycle and an 8-month seasonal demand cycle. The results of the study showed that the optimal cycle duration for components of categories B and C remains unchanged at 7 months, while the cycle for component A doubles in the seasonal scenario. This model makes long-term storage of the category A component impractical. Studies have confirmed that the Just in Time approach is more relevant for component A in the production of road pavement to minimise excess storage costs and maintain quality. It is determined that a combined approach maximises the efficiency of inventory management in producing road surfaces. ABC analysis identifies the key cost factor that requires Just in Time management to reduce storage costs. The Economic Optimal Quantity model is applied to components B and C, ensuring optimal ordering while maintaining operational efficiency. The study highlights the need to integrate multiple models to improve inventory decision-making in a dynamic manufacturing environment.

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Cherilya Alfara Natasya, Lilis Fitriyani, Putri Ayu Rukmini, Siti Santi, and Ujang Suherman. "Analisis Manajemen Persediaan Bahan Baku Pada UMKM Rengginang Berlian Kriuk di Karawang." Lokawati : Jurnal Penelitian Manajemen dan Inovasi Riset 2, no. 2 (2024): 188–96. http://dx.doi.org/10.61132/lokawati.v2i2.656.

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This research aims to determine the most effective inventory management in Rengginang Berlian Kriuk MSMEs. Using a qualitative descriptive approach, researchers analyze inventory management in Rengginang Berlian Kriuk MSMEs. The problem in this research is that Rengginang Berlian Kriuk MSMEs have not implemented raw material inventory management. The results of interview observations and documentation show that inventory management at Rengginang Berlian Kriuk MSMEs is not optimal. This is indicated by the minimal inventory available, because there are limitations in managing inventory. For this reason, researchers use safety stock and EOQ techniques to analyze inventory which can support inventory management effectively and efficiently.

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Dong, Li Li. "The Study on the Model of Vendor Management Inventory in Supply Chain." Applied Mechanics and Materials 644-650 (September 2014): 6105–8. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.6105.

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In order to reduce inventory cost effectively, the vendor management inventory (VMI) is studied in this paper. The inventory problem of supply chain is described, the model of VMI is established, and the optimal solution is obtained. The research in this paper can enrich the supply chain management theory, and help enterprises improve inventory management level.

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Rupanshu, Singh, and Jain Prasoon. "Inventory Management of Volvo Construction Equipment." Recent Trends in Production Engineering 4, no. 1 (2021): 1–10. https://doi.org/10.5281/zenodo.4835860.

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Manufacturing organisations are adapting the trend of lean methods to survive and compete in the dynamic market. The companies can evolve by meeting the needs of the customers and providing a satisfactory product, alongside this they can implement the lean optimalization methods to increase the efficiency. The aim of current research is to investigate the potential factors which affect the inventory size in the lean manufacturing environment, identify the perfect inventory management approach and develop an understanding of how the optimal inventory size can be achieved. A literature review was also performed to get an understanding of the current study on this topic. While gathering data, semi-structured interviews were conducted with engineering, line management and operations, observation technique was also used to collect empirical data. The inventory techniques were applied and satisfactory results were obtained.

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Kartikasari, Maya Andini. "Material Planning and Inventory Control in the Nutrition Service Unit at Ummi Hospital Bogor." Jurnal Logistik Indonesia 8, no. 1 (2024): 55–62. http://dx.doi.org/10.31334/logistik.v8i1.3857.

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Inventory management is a critical component of supply chain management that involves the planning, controlling, and overseeing of inventory levels to ensure the availability of materials while minimising costs. Proper inventory management ensures that essential food supplies are always available, allowing the hospital to provide consistent and varied meal options tailored to patient needs. Effective inventory management also ensures that there are no disruptions in meal service due to stockouts and avoids the capital and storage issues related to overstocking. This study aims to provide solutions to hospitals in terms of planning and controlling materials for the 2024 budget year so that hospitals can improve in terms of inventory management. The economic order quantity model is used to determine the optimal number of orders to be made to maintain inventory at a certain level while optimising inventory costs. The result showed that the optimal order quantity for chicken meat is 41 kg, beef is 21 kg, and rice is 112 kg, and the inventory cost incurred due to the stock is Rp. 170,000, Rp. 268,000, and Rp. 191,400, respectively.

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Anjani, Andan, and Adirizal Nizar. "Inventory management and cost efficiency." International Journal of Research in Business and Social Science (2147- 4478) 10, no. 2 (2021): 217–27. http://dx.doi.org/10.20525/ijrbs.v10i2.1042.

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This research aims to observe current inventory management applied by one of the medical equipment distributors specializing in eye health devices, and provide recommendations for an optimal inventory management system to achieve cost efficiency afterward. The method used in this research is quantitative, focusing on processing and analyzing numerical data obtained from the company to calculate safety stock and the number of orders. In addition, ABC classification is also used in data processing to group items based on their value. Items belonging to class A (having a value of 80% for the company) will be used in the data processing. The next step is to conduct forecasting simulations for demand forecasts. The results of the forecast will be used for calculating the safety stock and order quantity. The output from the results of data processing and analysis in this study shows 67 items included in class A, which will then be processed using Minitab software for forecasting. Based on comparing the four forecasting methods, the one with the lowest error value is Trend Analysis. If the company can apply the storage method according to the fixed-time period model calculation, there is a potential savings of US $ 717,133 or 63% of the total overstock

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RAMAKRISHNA, MR REGULAGADDA. "DYNAMIC INVENTORY MANAGEMENT USING AI." International Scientific Journal of Engineering and Management 04, no. 04 (2025): 1–7. https://doi.org/10.55041/isjem02874.

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Abstract: Efficient inventory management remains a critical challenge for organizations operating in fast-paced and uncertain supply chain environments. Traditional static inventory systems are increasingly insufficient in responding to fluctuating demand, supply variability, and dynamic market conditions. This paper presents a comprehensive study on the application of artificial intelligence (AI) techniques to enable dynamic inventory management systems. Leveraging machine learning algorithms, time-series forecasting, and reinforcement learning models, the proposed system adapts to real-time data inputs for accurate demand prediction, optimal replenishment decisions, and inventory cost minimization. The paper outlines the design and implementation of an AI-driven architecture integrating predictive analytics, sensor-based monitoring, and decision automation. Experimental validation demonstrates that the AI-enhanced system achieves significant improvements in forecast accuracy, reduces stockouts, lowers holding costs, and enhances responsiveness across varying supply chain scenarios. The findings suggest that AI-driven inventory systems offer a scalable and adaptive solution to meet the demands of modern, data-intensive logistics operations. The research contributes a novel framework for integrating AI in inventory control and provides insights into deployment challenges and strategic implications for businesses transitioning to intelligent supply chain solutions. Keywords: Artificial intelligence, inventory management, demand forecasting, dynamic systems, machine learning, supply chain optimization, reinforcement learning.

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Symonov, Denys, and Vasyl Gorbachuk. "A method of finding solutions in a dynamic model of inventory management under uncertainty." Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics, no. 4 (2022): 31–39. http://dx.doi.org/10.17721/1812-5409.2022/4.4.

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The article considers the method of finding solutions in the dynamic model of inventory management under uncertainty. An algorithm for formulating an optimal inventory management strategy is proposed using the developed method of determining the size of the optimal order lot and forming an optimal supply plan under conditions of stochastic demand. The developed solution is aimed at ensuring profit maximization in goods supply operations due to the optimization of inventory maintenance costs, an increase in inventory turnover ratio, a reduction of working capital maintenance costs, etc. The modelling was performed considering the mono-product strategy, the even distribution of sales in the cycle, and the instant supply of goods at the beginning of the cycle. The most common variables were listed as limitations of the model, which allows for a demonstration of the operation of the algorithm. The paper compares the simulation results of alternative methods of planning the inventory management process. The given results indicate the superiority of the proposed model.

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Andriansyah, Ari. "ANALISIS BIAYA PENJUALAN MENGGUNAKAN PERHITUNGAN POQ DALAM MERENCANAKAN DAN MENGENDALIKAN PERSEDIAAN POMPA AIR SUBMERSIBLE DI TOKO. XYZ." LAND JOURNAL 6, no. 1 (2025): 186–92. https://doi.org/10.47491/landjournal.v6i1.4009.

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Optimal inventory management is one of the key elements in supply chain management, especially for companies focusing on products with fluctuating demand, such as submersible water pumps. This study aims to analyze the planning and control of submersible water pump inventory at PT. XYZ using the Period Order Quantity (POQ) method. The POQ method was chosen for its ability to determine the optimal order quantity based on actual demand periods, thereby minimizing inventory costs, including ordering and holding costs. The analysis process begins by identifying historical demand data, inventory costs, and other relevant parameters. Subsequently, the POQ method is applied to calculate the optimal order quantity for each period based on demand levels and the ordering cycle time. The study's findings indicate that implementing the POQ method can reduce total inventory costs compared to conventional methods employed by the company. Moreover, this method enhances inventory management efficiency by reducing ordering frequency and the risk of stockouts. In conclusion, the POQ method has proven effective in helping PT. XYZ manage submersible water pump inventory more efficiently and economically. The study recommends developing an integrated inventory information system to support the sustainable implementation of this method.

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Cheng, Longsheng, Ching-Shih Tsou, Ming-Chang Lee, Li-Hua Huang, Dingwei Song, and Wei-Shan Teng. "Tradeoff Analysis for Optimal Multiobjective Inventory Model." Journal of Applied Mathematics 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/619898.

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Deterministic inventory model, the economic order quantity (EOQ), reveals that carrying inventory or ordering frequency follows a relation of tradeoff. For probabilistic demand, the tradeoff surface among annual order, expected inventory and shortage are useful because they quantify what the firm must pay in terms of ordering workload and inventory investment to meet the customer service desired. Based on a triobjective inventory model, this paper employs the successive approximation to obtain efficient control policies outlining tradeoffs among conflicting objectives. The nondominated solutions obtained by successive approximation are further used to plot a 3D scatterplot for exploring the relationships between objectives. Visualization of the tradeoffs displayed by the scatterplots justifies the computation effort done in the experiment, although several iterations needed to reach a nondominated solution make the solution procedure lengthy and tedious. Information elicited from the inverse relationships may help managers make deliberate inventory decisions. For the future work, developing an efficient and effective solution procedure for tradeoff analysis in multiobjective inventory management seems imperative.

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Ma, Le, and Yi Chai. "Modeling and Analysis of the Manufacturers Inventory in Closed-Loop Supply Chain." Applied Mechanics and Materials 541-542 (March 2014): 1507–12. http://dx.doi.org/10.4028/www.scientific.net/amm.541-542.1507.

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In this paper, the closed-loop supply chain inventory management as the research object, based on traditional inventory theory forward and reverse supply chain will be presented by combining deterministic closed-loop supply chain manufacturer's optimal inventory policy, determined by calculating the optimal production lot and do sensitivity analysis.

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