A Learning-Based Optimal Decision Scenario for an Inventory Problem under a Price Discount Policy

Author:

Momena Alaa Fouad1ORCID,Rahaman Mostafijur2ORCID,Haque Rakibul3ORCID,Alam Shariful2ORCID,Mondal Sankar Prasad3ORCID

Affiliation:

1. Department of Industrial Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Al Kharj 11942, Saudi Arabia

2. Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah 711103, India

3. Department of Applied Mathematics, Maulana Abul Kalam Azad University of Technology, Nadia, West Bengal, Haringhata 741249, India

Abstract

This paper aims to design an inventory model for a retail enterprise with a profit maximization objective using the opportunity for a price discount facility given by a supplier. In the profit maximization objective, the demand should be increased. The demand can be boosted by lowering the selling price. However, lowering the selling price may not always give the best profit. Impreciseness plays a vital role during such decision-making. The decision-making and managerial activities may be imprecise due to some decision variables. For instance, the selling price may not be deterministic. A vague selling price will make the retail decision imprecise. To achieve this goal, the retailer must minimize impreciseness as much as possible. Learning through repetition may be a practical approach in this regard. This paper investigates the impact of fuzzy impreciseness and triangular dense fuzzy setting, which dilutes the impreciseness involved with managerial decisions. Based on the mentioned objectives, this article considers an inventory model with price-dependent demand and time and a purchasing cost-dependent holding cost in an uncertain phenomenon. This paper incorporates the all-units discount policy into the unit purchase cost according to the order quantity. In this paper, the sense of learning is accounted for using a dense fuzzy set by considering the unit selling price as a triangular dense fuzzy number to lessen the impreciseness in the model. Four fuzzy optimization methods are used to obtain the usual extreme profit when searching for the optimal purchasing cost and sale price. It is perceived from the numerical outcomes that a dense fuzzy environment contributes the best results compared to a crisp and general fuzzy environment. Managerial insights from this paper are that learning from repeated dealing activities contributes to enhancing profitability by diluting impreciseness about the selling price and demand rate and taking the best opportunity from the discount facility while purchasing.

Funder

Prince Sattam Bin Abdulaziz University

Publisher

MDPI AG

Subject

Information Systems and Management,Computer Networks and Communications,Modeling and Simulation,Control and Systems Engineering,Software

Reference53 articles.

1. How many parts to make at once;Harris;Fact.-Mag. Manag.,1913

2. Hadley, G., and Whitin, T.M. (1963). Analysis of Inventory Systems, Prentice-Hall.

3. Naddor, E. (1966). Inventory Systems, John Wiley.

4. A heuristic for selecting lot size quantities for the case of a deterministic time varying demand rate and discrete opportunities for replenishment;Silver;Prod. Inventory Manag.,1973

5. An inventory model for deteriorating items with stock-dependent demand rate;Giri;Eur. J. Oper. Res.,1996

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