Warehouse Costs Research Articles

Deep reinforcement learning driven cost minimization for batch order scheduling in robotic mobile fulfillment systems

Robotic Mobile Fulfillment Systems (RMFS) are extensively employed in modern warehouses. In the era of booming e-commerce, this parts-to-picker model significantly reduces warehouse costs and enhances operational efficiency. The primary focus of this article is on the scheduling of batch orders, which involves the simultaneous allocation of mobile robots and picking stations to orders to meet their requirements, with the aim of minimizing processing costs. While the optimization of RMFS has been extensively investigated by scholars in recent years., research on categorized storage remains limited. Furthermore, combinatorial optimization in scenarios with large orders, numerous picking stations, and multiple mobile robots presents an ongoing and significant challenge. To overcome these challenges, we introduce the Enhanced Deep Reinforcement Learning Method for Batch Order Scheduling (EDRL-OBOS), designed to minimize operational costs in RMFS. Our proposed algorithm, EDRL-OBOS, features a uniquely designed state space that encompasses the allocation of all orders, with the variable portion of the state space diminishing as the algorithm evolves. Moreover, we substitute traditional actions with heuristic rules, significantly enhancing the efficiency of the algorithm. Additionally, we establish a reward function based on a greedy algorithm, ensuring that our method surpasses conventional algorithms. As the number of episodes progresses, the EDRL-OBOS algorithm assigns picking stations and sequences of mobile robots to each order until all orders within the state space are fulfilled, subsequently determining the reward. Subsequently, all states are reset to their initial conditions, and the order allocation scheme is optimized through the learning experience from the previous episode, until convergence is reached. Ultimately, we conduct simulation experiments by varying the number of orders, picking stations, and mobile robots. The results indicate that the EDRL-OBOS algorithm achieves a maximum cost reduction of 22.89%, a minimum of 19.66%, and an average of 21.57%, across various scenarios. At the same time, the computation of our algorithms is superior to that of traditional algorithms.

Sustainable Design and Construction Cost of Warehouse in the Light of Applicable Fire Regulations

This paper examines the effectiveness of sustainable warehouse design with regard to fire regulations and costs. When designing industrial facilities, the high risk of fire during their subsequent operation must be considered. Therefore, in this article, the variant analysis in terms of cost and technological, sustainable solutions for the investment in the “design and build” system were subjected to fire protection installation systems for three variants with different fire zones. During the modelling, the impact of the fire zone on the spread of smoke, temperature changes at a selected point above the fire source, and visibility were examined. Numerical analyses showed differences in the degree of smoke spread for variants I, II, and III without any relevant impact on the effectiveness of evacuation. The division of the hall into a larger number of fire zones reduces the effects of a potential fire. This study highlights that the cost of the investment is vastly influenced by the conditions of fire protection and evacuation.

Modelling a sorghum logistics as a substitution of wheat to encourage food diversification program and enhance the productivity of local crops

the current diet trend in Indonesia suggests noodles made from wheat as the alternative to rice. This condition leads Indonesia to import the wheat as much as 11.5 million tonnes per year. In fact, Indonesia has become the world’s second largest wheat importer and ranks among East Asia’s largest staple food importers, mainly for wheat. The distribution of wheat commodity is being hampered due to the conflict between Russia and Ukraine, both of whom are major wheat suppliers in global market. As a solution, President of Indonesia, declaring a means to utilise other crops or implementing food diversification by using sorghum. Sorghum is a grain that able to thrive in tropical and dry areas, such as Indonesia and is possible to substitute that of some wheat. This final project aims to plan door to door sorghum logistic model whenever used as a substitution of wheat in a dry noodle factory located in Sidoarjo Regency by acquiring the lowest cost and a scheduling of sorghum deliveries to fulfil daily demand of the factory itself. The method applied to model the logistic planning is Vehicle Routing Problem (VRP) to determine which scenario giving the most minimum cost. The result of the analysis performed showing that the operational pattern chosen is port to port with voyage charter option obtained a freight cost of Rp17.549.076.988 or a unit cost of Rp558.571 /ton. The scheduling model shows that scenario of warehouse renting in every field is chosen and by doing the sensitivity analysis giving the total cost of Rp11.566.026.812 which includes trucking cost, warehouse cost, and stacking cost. The result shows the overall cost of the sorghum logistic model is Rp29.115.103.800 or equal to Rp926.708 /ton. Furthermore, the partial substitution of sorghum flour for wheat flour results in an 9,81% rise in production costs

ДОСЛІДЖЕННЯ КОНСТРУКЦІЙ ЗАПОБІЖНИХ ПРИСТРОЇВ ПІДЙОМНИХ МАШИН

The article examines the designs of support structures for the re-installation of lifting machines, which are mounted on suspended ropes. The object of investigation is theft, which stems from the costs of the rope suction block of an overhead crane. The method of work is to track warehouse costs on the rope suction block of an overhead crane, which affects the accuracy and reliability of the work of the associated device. It has been established that up to a short period of time this type of structure exhibits a loss of vibration in the range of 5 - 6 %, which is due to the influx of additional forces on the transmission elements of the secondary device. However, due to its reliability, simplicity and low cost of construction, there has been a wide expansion in the crane industry. Investigations of the losses that occur when the tension of the rope is tightened, which is due to the instrumental deformation of the device, and methodically, which arises from the chopping of the diameter of the rope in order to reach the end of its life, hitting the block and spending on blocks. Removing the analytical significance of the significant losses that result from the expenses on the rope ventilating block of the lifting machine. A full-scale testing of an external device for overhead cranes of the vantage type with a capacity of up to three tones was carried out. The test results confirmed the accuracy and reliability of application for this type of assistant. To reduce the damage caused by friction in the bearings of the block and on the heeled rigidity of the rope, it was necessary to install an additional device in the place where the rope is secured.

Management of spare parts for efficient maintenance: a case study in the dairy sector

The recent increase in automation in production systems increased the relevance of maintenance management and spare parts availability to improve productivity while reducing the downtimes of the equipment. Despite the large number of studies on the topic, there is still a lack of practical applications in the industrial environment which can underline real practical needs and not only theoretical ones. The objective of this study is to improve the management of the spare parts warehouse of a company in the dairy sector to support maintenance management, defining optimal reorder quantities and/or safety stocks to minimize warehouse costs and increase component availability, especially of those items considered most critical. The practical work concerned the coding and classification of the spare parts, the demand forecasting, the definition of the most appropriate inventory policy for each spare part, and finally the testing and validation of the proposed policies.

A deep reinforcement learning based algorithm for a distributed precast concrete production scheduling

The environmental-friendly production demands higher manufacturing efficiency and lower energy cost; therefore, time-of-use electricity price constraint and distributed production have attracted more attention. For concrete precast architecture construction, the tardiness penalty and warehouse cost cannot be ignored, which should be optimized for lower cost. In this study, the concrete precast process is investigated as the group scheduling of a distributed flexible job shop problem. Each concrete precast is managed in a group, the setup time between different groups is considered. Two objectives, total weighted earliness and tardiness and total time-of-use electricity cost are minimized, simultaneously. To solve the integrated problem, three coordinated double deep Q-networks (DQN) are applied, which are organized as a learn-to-improve reinforcement learning approach. For distributed scheduling problem, operators in a single factory or in multiple factories differs in solution improvement; so selection DQN is designed to decide the type of the operators according to scheduling circumstances. Other two DQNs, i.e., local DQN and global DQN, are to select the optimization operators in one factory or in multiple factories, respectively. Furthermore, two solution refinement strategies are designed to decrease the objectives after reinforcement learning component. Numerical experiment and statistical analysis suggest that the proposed deep reinforcement learning based algorithm has superiority in solving the considered problem.

A fuzzy multiobjective linear programming approach for green multiechelon distribution network design

PurposeDistribution network design involves a set of strategic decisions in supply chains because of their long-term impacts on the total logistics cost and environment. To incorporate a trade-off between financial and environmental aspects of these decisions, this paper aims to determine an optimal location, among candidate locations, of a new logistics center, its capacity, as well as optimal network flows for an existing distribution network, while concurrently minimizing the total logistics cost and gas emission. In addition, uncertainty in transportation and warehousing costs are considered.Design/methodology/approachThe problem is formulated as a fuzzy multiobjective mathematical model. The effectiveness of this model is demonstrated using an industrial case study. The problem instance is a four-echelon distribution network with 22 products and a planning horizon of 20 periods. The model is solved by using the min–max and augmented ε-constraint methods with CPLEX as the solver. In addition to illustrating model’s applicability, the effect of choosing a new warehouse in the model is investigated through a scenario analysis.FindingsFor the applicability of the model, the results indicate that the augmented ε-constraint approach provides a set of Pareto solutions, which represents the ideal trade-off between the total logistics cost and gas emission. Through a case study problem instance, the augmented ε-constraint approach is recommended for similar network design problems. From a scenario analysis, when the operational cost of the new warehouse is within a specific fraction of the warehousing cost of third-party warehouses, the solution with the new warehouse outperforms that without the new warehouse with respective to financial and environmental objectives.Originality/valueThe proposed model is an effective decision support tool for management, who would like to assess the impact of network planning decisions on the performance of their supply chains with respect to both financial and environmental aspects under uncertainty.

Research on AGV cart control system based on fuzzy PID control

Abstract As an important carrier of intelligent logistics, AGV can effectively reduce the labor cost of factories and warehouses. With the comprehensive promotion of “smart manufacturing”, the manufacturing industry has a stronger demand for automated AGV logistics systems. This paper firstly analyzes the principle of fuzzy PID controller and establishes its kinematic model to obtain the intrinsic relationship between the motion form and the speed of each driving wheel. Secondly, through the data measured and fed back by the fuzzy PID control system, the AGV driving angle deviation and position deviation are used as the input of the fuzzy controller; its fuzzy deviation correction technology is applied to realize the path correction of the AGV and ensure the stable operation of the AGV through the cooperative motion control technology. Finally, MATLAB software establishes the joint simulation model of the AGV fuzzy PID control system. The results show that through the two algorithms of PID control and fuzzy PID control correction test, the fuzzy PID controller system corrects the deflection efficiency by 47.41%; in the kinematic test, the path tracking efficiency is increased by 30.76%, the distance correction efficiency is increased by 69.56%, the angle correction efficiency is increased by 69.56%, and the average performance is increased by 53.44%. Through the two comparisons, it is concluded that the fuzzy controller designed in this paper has the advantages of fast response speed, good stability, and strong deflection correction performance, which substantially improves the speed and accuracy of intelligent search of intelligent vehicles.

Sales forecasting using machine learning algorithms

Retail companies, as production systems, must use their resources efficiently and make strategic decisions to obtain growing and stable revenues, especially when market conditions are becoming more competitive and profit margins are increasingly pressured. Thus, sales forecasting is crucial to maintain competitiveness in the retail segment, but obtaining inaccurate forecasts can lead to stock shortages, causing delays in deliveries and generating customer dissatisfaction, as well as increasing inventory, increasing the cost of warehousing, forcing the “burn” of stock through promotional campaigns, directly affecting profitability. Forecasting the demand for products and services and adapting the supply chain by finding a balance has always been and will continue to be a challenge in the retail segment. This research aims to evaluate the main methods and identify the one with the greatest accuracy in sales prediction. Based on an integrative literature review (ILR), three main methods were evaluated: time series, artificial neural networks and machine learning algorithms. The results show that machine learning is more suitable in terms of accuracy, particularly when models contain exogenous and endogenous variables, in addition to allowing the identification of hidden patterns in demand that can be used to identify market trends. However, in markets with constant demands and few external interferences, its use is not justified because, for these cases, the use of time series is simpler and less costly.

Research on Logistics Warehousing Cost of Z Delivery Enterprise and Its Optimization Strategy

Aiming at the fierce price competition in the logistics industry, this paper studied the logistics storage of Z Express enterprises. First, according to the current situation of the logistics enterprise, the current storage problems were found out. To discuss its storage cost in depth, the analysis is carried out from two aspects: the internal structure of storage cost and the external factors. The former uses the activity-based cost method to analyze, and is supplemented by peer benchmark comparison. The latter directly proposes countermeasures based on related issues. Finally, using fuzzy comprehensive evaluation to evaluate the proposed optimization strategy, in order to find an accurate method to optimize the logistics storage cost of Z Express enterprise.

ОЦІНКА ЕФЕКТИВНОСТІ ЛОГІСТИЧНОЇ ДІЯЛЬНОСТІ ПРОМИСЛОВОГО ПІДПРИЄМСТВА ASSESSMENT OF THE EFFICIENCY O

The article is devoted to the actual issues of evaluating the efficiency of logistics activities of an industrial enterprise. The main methodical approaches for assessing the efficiency of logistics activities of enterprises in modern conditions are presented and characterized. Usage of an improved methodology is proposed and substantiated for assessing the efficiency and reliability of logistics activity. The methodology for evaluating efficiency and reliability is based on the analysis of the structure of logistics costs in relation to profit. Profit is calculated by allocating them according to the articles of the financial results report: general production costs, administrative costs and sales costs. Logistics costs include costs for logistics administration and material flow management as part of administrative costs. Logistics costs include warehouse costs, transportation costs, and loading/unloading costs as part of sales costs. Logistics costs include supply costs, production logistics costs and service costs as part of general production costs. The methodology takes into account the peculiarities, influencing factors and other factors of the industrial enterprise. It is proposed to use indicators for a comprehensive assessment of the efficiency of the logistics system by its elements (supply, production, transportation, storage, marketing). The complex indicator is calculated for the efficiency of the logistics activity of the enterprise according to the formula of the geometric mean. The integral indicator of the efficiency of the logistics activity of the enterprise is calculated as the geometric mean of the integrated indicator of the efficiency of the logistics activity over the years of research. It is expedient to assess the reliability of the enterprise's logistics activities for each group of indicators using the coefficient of variation. The higher the rate of variation, the less reliable a particular logistics system is. An assessment of the efficiency and reliability of logistics activities at a specific industrial enterprise was carried out using the proposed methodology.

Pureshare Method in Dashboard Development to Monitor Warehouse Performance at PT XYZ Using the Cost Per Case (Cpc) Perspective

Warehouse costs contribute about 22% of the company's total logistics costs. Thus, a warehouse manager must have comprehensive knowledge of costs and cost triggers in the warehouse to be able to minimize costs while keeping customer satisfaction. One effective way to minimize warehouse costs is by conducting the cost analysis. Although PT XYZ is one of the biggest Fast Moving Consumer Goods (FMCG) companies in Indonesia applying one of the most comprehensive Enterprise Resource Planning software, its existing warehouse management support system occupies only standard Microsoft Excel. One of its warehouses, located in West Java, is responsible for more than 147,000 pallets each day, and the warehouse manager still uses Microsoft Excel with limitations in displaying the required information, especially the information related to the Cost Per Case (CPC) in every activity. Therefore, a template or dashboard that can provide information related to CPC in the warehouse is urgently needed. Given the importance of cost monitoring in the warehouse of PT XYZ, this research aims to create a dashboard that can make it easier for companies to monitor warehouse performance from a CPC perspective. The methods used in data collection consist of several processes, namely interviews, observations, and literature studies. While analyzing the needs of dashboard creation, this research uses the PureShare method. Thus, the results are obtained in the form of a proposed warehouse dashboard that can be used by the company to conduct cost analysis by providing information related to CPC of every activity in the warehouse, where the information presented on the dashboard is in accordance with the company's needs.

ЗАСТОСУВАННЯ ЛОГІСТИЧНИХ МЕТОДІВ ДЛЯ ВПРОВАДЖЕННЯ CROSS-DOCKING ТЕХНОЛОГІЇ В ТРАНСПОРТНО-СКЛАДСЬКІЙ СИСТЕМІ

Abstract Introduction. The efficiency of logistics operations, the speed of processing of goods largely depend on how all parts of the logistics chain interact, how optimized business processes in the warehouse, so any company tries to constantly improve the organization of the supply process so as to deliver in the shortest possible time. term for minimum logistics costs. One of the tasks to solve the problem of supply chain imperfections is to reduce the huge number of warehousing operations during the placement of goods for long-term or short-term storage. This can be done with the help of Cross-Docking technology, which eliminates the storage phase and reduces warehousing costs. Problem statement. Today, Cross-Docking technology is mobile, technologically proven, because it is a very advanced method of processing goods. However, in order to successfully implement this technology, it is necessary to understand the concept of Cross - Docking, knowledge of the features, benefits, conditions and limitations for the implementation of this technology. That is why the question of determining the list of goods for which the introduction of this Cross - Docking technology is expedient and rational is becoming relevant. Purpose. To substantiate the definition of the list of goods for which the introduction of Cross-Docking technology is expedient and rational, using the coefficient of variation and making recommendations for their processing and methods of handling - by grouping by logistic method XYZ analysis. Methods. The XYZ analysis method was used during the work. Results. The study justified the use of the coefficient of variation to identify goods for which it is appropriate and rational to implement Cross-Docking technology, and the use of logistics method - XYZ analysis - to develop recommendations for processing and handling of certain goods. Conclusions. Based on research based on theoretical and applied aspects, the development and implementation of Cross - Docking technology is an element that simplifies business logistics and reduces the cost of its products by reducing warehouse costs, and properly organized process speeds up delivery, allows businesses to send perishable products over long distances and organize turnover even in high season. The proposed logistic method of differentiation by HYZ analysis allows to clearly identify those products that are characterized by maximum demand, high turnover, stable predictability, mass consumption, ie those products for which the recommendation is to minimize their number in warehouses, respectively - the feasibility and rationality of Cross technology - Docking. Key words: supply chain, Cross - Docking technology, one - stage Cross - Docking, two - stage Cross - Docking, XYZ - analysis, coefficient of variation, methods of grouping in XYZ - analysis, XYZ - analysis solutions.

Industrial vehicle routing problem: a case study

This study is motivated by a real-world application of ABC (Pvt) Ltd., a well-known FMCG (fast-moving consumer goods) industry. The industry have nine agents (in two operating regions) from which it can serve its 5483 clients. We focus on this industry’s outbound logistics in its two operating regions, namely Colombo and Gampaha, while taking into account its distribution and current decentralized redistribution processes, since additional routing costs have been identified in the existing setup. The goal of this study is to implement a better route plan that optimizes the truck allocation system at the lowest possible costs of transportation, warehouse, and administration. First to determine a best location for the new facility, the gravity model is used to pinpoint the exact location of the central warehouse. Then a centralized delivery strategy is applied to establish a better path between the sub-clusters. The performance of this centralized policy is evaluated on a real-world case study data. The relative cost benefit/saving (34%) of the centralized distribution system is then brought into focus and verified with solid statistics by comparing the overall cost of the centralized distribution system to the total cost of the existing decentralized distribution system. Finally, we highlight how decision-makers and policymakers in the logistics area might use our centralized delivery strategy to reduce extra-costs, particularly during the transportation of commodities.

Sustainable development of logistics systems: features of accounting and cost analysis

Optimal and lower prime cost with maintaining quality is one of the important competitive advantages of the enterprise. With this in mind, it is necessary to manage logistical costs, using accounting as one of the tools for planning, analysis, and optimisation of these costs. The purpose of the paper is to study the directions for organising the accounting and to analyse the logistical costs in the framework of sustainable development in terms of transport and warehouse logistics for Ka-zakhstani enterprises. A review of the methodology for accounting for logistical costs, options for such accounting was carried out, 10 enterprises operating in the field of Internet trading in Kazakhstan were studied, their approaches to organising various types of logistical costs were investigated, problems were identified and directions for improvement related to the detailing of accounting purchase of goods), warehouse costs, as well as the use of a planning and analysis system for logistical costs, including financial and opportunity costs associated with the amount of balances and goods turnover in the warehouse. According to the results of the study, it was proposed to use different subsidiary accounts to account for goods at the purchase value billed by the supplier and the costs of delivery to the company's warehouse in order to highlight the logistical costs. Also detailing of ac-counting for warehouse logistical costs is proposed (allocation of sub-accounts for accounting for fixed and variable costs of the warehouse).

Logistics model for precast concrete components using novel hybrid Ant Lion Optimizer (ALO) algorithm

Precast concrete component utilization for building projects has been considered to become the leading trend in construction industry around the world. The logistics costs for precast concrete elements have usually accounted for a large proportion in whole costs executing projects. According to previous studies of logistics cost optimization that have been focused on the costs of transportation and warehouse, however, other necessary costs have not been examined carefully as costs of purchase, depot, load and unload, installation. Therefore, this study provides the comprehensive model of logistics expenditures for precast concrete structures using the Activity-based costing (ABC) method. Also, this study develops the ALO algorithm by hybriding with other algorithms as opposition-based learning, mutation and crossover strategy to optimize costs based on ABC. By evaluating and comparing with previous study applying the genetic algorithm GA, the particle swarm optimization (PSO), the gray wolf algorithm (GWO) and the dragonfly-particle swarm optimization (DA-PSO) the conclusion has generated the superior results in terms of convergence speed, the high degree of accuracy and reducing the logistic cost.

ЭКОНОМИЧЕСКАЯ ЭФФЕКТИВНОСТЬ СОВЕРШЕНСТВОВАНИЯ ЛОГИСТИЧЕСКОГО УПРАВЛЕНИЯ В ОРГАНИЗАЦИИ

The article considers the possibilities of purposeful influence on all parts of the supply chain to promote commodity flows from the producer to the final consumer. The current development tasks are identified and various options for implementing software for the organization's logistics activities are considered. It is necessary to organize the activities so that all the processes together lead to the minimization of warehouse costs. Cost reduction reserves may be located in the area of cost optimization that is not directly related to customer service. To determine the method of automation, several possible options were analyzed and their economic feasibility was determined. The first option is the introduction of a warehouse management system based on the Logistics Information System BIT. The second option is to modify the existing accounting program 1C SCP to meet the requirements of the organization. The third option is the implementation of a warehouse management system based on the software product 1C: WMS Logistics. Warehouse management 4.Offer. The article substantiates a promising system of logistics management in the organization based on the optimization of the processes of making and implementing management decisions aimed at improving the efficiency of the warehouse management of the enterprise.

The average-cost formulation of lot sizing models and inventory carrying charges: a technical note

It is generally recognised that the present-value criterion should be preferred to the average-cost formulation in developing lot sizing models. Despite the advantages of the present-value measure, average-cost lot sizing models are far more widely applied. Because of the nature of the average-cost formulation, inventory carrying costs are evaluated according to a look-back approach, relying on historical values. In this regard, a general misconception in the inventory management literature concerned with average-cost models is that the unit stockholding cost rate should be established considering fixed warehouse costs, which are costs that are, in the short term, independent of the inventory level. This paper develops arguments supporting our belief that inventory carrying charges used in lot sizing models should take into account only those costs varying with the inventory level in the warehouse, and that considering fixed warehouse costs leads to pitfalls when making inventory replenishment decisions. To this aim, we first present an analytical treatment based on the classical Economic Order Quantity (EOQ) model, as its full analytical tractability permits us to better discuss the problem we are interested in. Finally, we present numerical experiments to assess the effect of the correct procedure to establish the unit stockholding cost rate on inventory management decisions. These experiments are performed considering warehouse costs taken from some industrial case studies presented in the literature.

Modeling Single-Picker Routing Problems in Classical and Modern Warehouses

The standard single-picker routing problem (SPRP) seeks the cost-minimal tour to collect a set of given articles in a rectangular single-block warehouse with parallel picking aisles and a dedicated storage policy, that is, each stock-keeping unit is only available from one storage location in the warehouse. We present a compact formulation that forgoes classical subtour elimination constraints by directly exploiting two of the properties of an optimal picking tour used in the dynamic programming algorithm published in the seminal paper of Ratliff and Rosenthal. We extend the formulation to three important settings prevalent in modern e-commerce warehouses: scattered storage, decoupling of picker and cart, and multiple end depots. In numerical studies, our formulation outperforms existing standard SPRP formulations from the literature and proves able to solve large instances within short runtimes. Realistically sized instances of the three problem extensions can also be solved with low computational effort. For scattered storage, we note a rough tendency that runtimes increase with longer pick lists or a higher degree of duplication. In addition, we find that decoupling of picker and cart can lead to substantial cost savings depending on the speed and capacity of the picker when traveling alone, whereas additional end depots have rather limited benefits in a single-block warehouse. Summary of Contribution: Efficiently routing order pickers is of great practical interest because picking costs make up a substantial part of operational warehouse costs. For the prevalent case of a rectangular warehouse with parallel picking aisles, we present a highly effective modeling approach that covers—in addition to the standard setting—several important storage and order-picking strategies employed in modern e-commerce warehouses: scattered storage, decoupling of picker and cart, and multiple end depots. In this way, we provide practitioners as well as scientists with an easy and quick way of implementing a high-quality solution approach for routing pickers in the described settings. In addition, we shed some light on the cost benefits of the different storage and picking strategies in numerical experiments.

Проблеми та шляхи підвищення ефективності управління запасами торговельного підприємства

The article defines the economic essence of stocks from the point of view of domestic and foreign scholers, as well as in accordance with the legislation of Ukraine. It is specified that the main form of sale of inventory are independent wholesale and retail trade enterprises. The detailed classification of stocks, which is necessary to track the dynamics of consumer demand and planning rational volumes of purchase of products, which is important for ensuring uninterrupted sale, is considered. The main models and systems of inventory management are analyzed, such as the system with the established volume or size of the order, the system with a certain frequency of the order, the model of the optimal size of the Harris – Wilson order. The main tasks of inventory management at the enterprise are determined as follows: minimization of warehouse costs for storage of goods by accelerating the turnover of inventory; ensuring the optimal number of goods that can be sold in the near future and will bring profit. Thus, it was clarified that the main purpose of inventory management is to form and maintain their value at a level that allows for uninterrupted trade in each product at minimal cost. The process of choosing the optimal level of stocks is considered. An ABC- and XYZ-analysis based on commodity stocks of LLC «RUSH» is carried out. Recommendations for the management of different groups of goods are elaborated. It is defined that it is extremely important for any trading network to find the optimal combination between the costs and benefits of the selected level of inventories in order to determine what value of stocks for each product group or even a goods item is sufficient, as well as to choose the correct inventory management model for each category of goods.