Changing economic conditions make the selling price and demand quantity more and more uncertain in the market. The conventional inventory models determine the selling price and order quantity for a retailer’s maximal profit with exactly known parameters. This paper develops a solution method to derive the fuzzy profit of the inventory model when the demand quantity and unit cost are fuzzy numbe...

⎯This study addresses the problem of complete pre-ordered merchandise supply. We discuss the sale price and the supply period with the demand rate function of merchandise for customers and the ratio function of customers’ willingness to wait for taking merchandise, wherein the supply period and the sale price at any point of time during the complete stock-out period are decision variables. The ...

In this paper, a Back Propagation-Artificial Neural Network (BPANN) has been adapted for predicting the required car parts quantities in a real and major auto parts supplier chain. The conventional approach to determine the parts requirements is the Economic Order Quantity (EOQ) method. The ability of neural models to learn, particularly their capability of handling large amounts of data simult...

This study revisits a fuzzy rough economic order quantity (EOQ) model for deteriorating items considering quantity discount and prepayment. Since the proposedmodel is amixed integer nonlinear programming type, it is solved using Meta heuristic algorithms. Based on three different case examples, we have shown that our results using the Bees Colony Optimization (BCO) algorithm performs better tha...

The purpose of this study was to analyze raw material inventory control with the Economic Order Quantity (EOQ) method on CV. BJT 47 Embroidery Sukabumi City. research used is descriptive quantitative describe and data. data processed using EOQ determine total cost inventory. results show that there a large difference if method, savings are more efficient. conclusion by applying we can optimize ...