Abstract
In modern business today, organizations that hold large numbers of inventory items, do not find it economical to make policies for the management of individual inventory items. Managers, thus, need to classify these items according to their importance and fit each item to a certain asset class. The method of grouping and inventory control available in traditional ABC has several disadvantages. These shortcomings have led to the development of an optimization model in the present study to improve the grouping and inventory control decisions in ABC. Moreover, it simultaneously optimizes the existing business relationships among revenue, investment in inventory and customer satisfaction (through service levels) as well as a company’s budget for inventory costs. In this paper, a mathematical model is presented to classify inventory items, taking into account significant profit and cost reduction indices. The model has an objective function to maximize the net profit of items in stock. Limitations such as budget even inventory shortages are taken into account too. The mathematical model is solved by the Benders decomposition and the Lagrange relaxation algorithms. Then, the results of the two solutions are compared. The TOPSIS technique and statistical tests are used to evaluate and compare the proposed solutions with one another and to choose the best one. Subsequently, several sensitivity analyses are performed on the model, which helps inventory control managers determine the effect of inventory management costs on optimal decision making and item grouping. Finally, according to the results of evaluating the efficiency of the proposed model and the solution method, a real-world case study is conducted on the ceramic tile industry. Based on the proposed approach, several managerial perspectives are gained on optimal inventory grouping and item control strategies.
Highlights
In today’s industrialized world, given the intense industrial competition, it is crucial to pay attention to inventory control and the proper control of all types of organizations, especially manufacturing ones
As the insights suggest, (a) when the overhead cost in a group is reduced, it is advisable to have more classified groups for the inventory, (b) the proposed model decreases return on investment (ROI) in the net profit and helps organizations justify the benefits of increased inventory budgets, (c) when the budget is limited, it is more likely to grow the number of inventory class groups; in contrast, when a large budget is available, it may be possible to classify items into fewer groups, which is a feature of the traditional ABC approach, and (d) if there is a high cost for inventory shortages, it makes sense to increase profits, but considering its low cost has no significant impact on the net profit
The mathematical model was run for 10 different numerical examples, and the results of the two suggested solutions were statistically compared through a t-test
Summary
In today’s industrialized world, given the intense industrial competition, it is crucial to pay attention to inventory control and the proper control of all types of organizations, especially manufacturing ones. Other methods have been presented in recent years to classify ABC multi-criteria inventories In this regard, one may refer to the analytic hierarchy process (AHP), artificial intelligence techniques, statistical analysis, data envelopment analysis (DEA) [12], weighted Euclidean distance, standard criterion matrix model, cluster analysis model, meta-heuristic algorithms, optimization algorithms, ABC-FUZZY classification approach, and multiple criteria decision aiding (MCDA). This process can be tedious when there are too many items in stock, which may even lead to infeasible solutions These shortcomings have led to the development of an optimization model in the present study to improve the grouping and inventory control decisions in ABC. Section eight recounts the conclusions of the study and provides some suggestions for future research
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
