This paper develops an artificial neural network (ANN) model to forecast the optimum level of raw materials inventory as a function of product demand, manufacturing lead-time, supplier reliability, material holding cost, and material cost. The model selects a feed-forward back-propagation ANN with twelve hidden neurons as the optimum network. We test the model with pharmaceutical company data. ...

Starting in the 1960s, a number of academic works have focused in serial and distributed multi-echelon structures and in both deterministic and stochastic environments. Clark and Scarf (1960, 1962) developed a seminal work in which they presented optimal policies for a serial multi-echelon system. Schwartz (1973) studied a deterministic model having one warehouse and N retailers and showed that...

In general, a supplier/retailer frequently offer trade credit to stimulate their respective sales. The main purpose of this paper is to investigate the optimal supplier/retailer’s replenishment decisions under two levels of trade credit policy within the economic order quantity (EOQ) framework. This paper deals with the supplier/retailer’s inventory replenishment problem under two levels of tra...

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 research to determine the policy of controlling raw material inventory in a company if it uses Economic Order Quantity (EOQ) method with current policy. The data used form about main needs and costs incurred ordering storing during 2017-2019. Data collection techniques by examining documents. is descriptive discussion that make systematic picture using object under study. results analysi...

Variability of demand for goods, depending on their availability and cost is a frequently observed phenomenon in the sphere production consumption. This paper discusses possibility using ABC analysis inventory management system. type makes it possible to apply various methods increasing income reducing costs particular products manufacturers.
 As known, process approach emphasizes systemat...

Military clothing retailers employ a traditional Economic Order Quantity (EOQ) strategy, producing infrequent, large orders that cause serious production scheduling and delivery problems for manufacturers, producing what is sometimes called the bullwhip effect. These problems delay manufacturer response and cause stock outages at the retailer. This paper describes a decision support system that...

In this paper, the study attempts to determine the optimal capital investment in setup cost reduction and optimal lot sizing policies for an economic order quantity (EOQ) model with random yields. The setup cost is treated as the function of capital expenditure in technology. The study shows that the expected total annual cost functions with capital investment is convex and develop a solution p...

This paper develops an economic order quantity (EOQ) model with uncertain data. For modelling the uncertainty in real-world data, the exponents and coefficients in demand and cost functions are considered as interval data and then, the related model is designed. The proposed model maximises the profit and determines the price, marketing cost and lot sizing with the interval data. Since the mode...

We developed an economic order quantity (EOQ) model with a learning effect and carbon emissions under inflationary conditions inspection for retailers where the items deteriorate naturally. Finally, total profit of retailer is maximized respect to cycle length. A sensitivity analysis was also performed understand robustness model. In analysis, we discuss impact rate, inflation deterioration rat...