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...

We consider a continuous-review inventory model for a firm that faces deterministic demand but whose supplier experiences random disruptions. The supplier experiences “wet” and “dry” (operational and disrupted) periods whose durations are exponentially distributed. The firm follows an EOQ-like policy during wet periods but may not place orders during dry periods; any demands occurring during dr...

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...

In this paper, we have considered an economic order quantity model for deteriorating items with two-level trade credit policy in which a delay in payment is offered by a supplier to a retailer and also an another delay in payment is offered by the retailer to his/her all customers. Here, it is proposed that the demand function is dependent on the length of the customer's credit period and also ...

Inventory of raw materials or at PT. PGP has not been planned properly so that one time the run out during production process. management applied by company paid attention to economical order quantity, and also point reordering materials. This course an impact on additional costs should be needed, in other words it is effective efficient, sees need apply EOQ method managing study aims determine...