جستجوی مقالات مرتبط با کلیدواژه « Delayed Payment » در نشریات گروه « صنایع »

In classic inventory control system، purchasing cost must be paid when purchased items are received. Furthermore، in the mentioned models، items may have infinite lifetime، while in the real world، we have some items deteriorate over the time. Also، in order to increase the sales، the suppliers may allow the retailers to pay the purchasing cost some times after receiving the ordered products. Moreover، in the real life cases، the supplier may visit the retailer and send the ordered quantity at random time and the retailer faces to stochastic lead time; then، in this case، the retailer may face to shortage. In this paper، we will extend the periodic inventory control model under delay in payment، stochastic visit interval and partial backordering for a deteriorating item. Under general probability distribution function between replenishment epochs، we show the concavity of the expected profit function and give the condition that must hold for the optimal replenish-up-to-level in order to maximize the profit. In order to show the applicability of the proposed model، the numerical examples and sensitivity analysis are provided.

In classic inventory control system, we assume that purchasing cost should be paid at time of delivery. But sometimes in order to encourage retailer to increase his order, postpond payment is provided by supplier as an incentive policy for retailer. In this paper a periodic inventory control model is invetigated in which the period between two consecutive replenishmnet is a random variable. In fact the economic order quantity model under stochastic period lenght and postpond payment is developed. In this paper the concavity of profit function is prooved and situation under which the profit function of retalier is maximized, is determined. The aim of this researchis to determine the the maximum level of inventory such that the total profit is maximized. In continue in order to describe the model numerical examples and sensitivity analysis are introduced.