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All units discount: an order of 1–1000 units costs $50 each; an order of 1001–5000 units costs $45 each; an order of more than 5000 units costs $40 each. So when 1500 units are ordered, the total cost is $45*1500.
In (), the first order loss function [(,)] captures the expected shortage quantity; its complement, [(,)], denotes the expected product quantity in stock at the end of the period. [ 10 ] On the basis of this cost function the determination of the optimal inventory level is a minimization problem.
The disadvantages of planning a small batch are that there will be costs of frequent ordering, and a high risk of interruption of production because of a small product inventory. [12] Somewhere between the large and small batch quantity is the optimal batch quantity, i.e. the quantity in which the cost per product unit is the lowest. [12]
The general cost per kiosk is difficult to quantify, with one manufacturer estimating a range of $1,500 to $20,000 per station. However, with the use of kiosks, restaurants may not need as many ...
Therefore, in order to get the optimal production quantity we need to set holding cost per year equal to ordering cost per year and solve for quantity (Q), which is the EPQ formula mentioned below. Ordering this quantity will result in the lowest total inventory cost per year.
There is a setup cost s t incurred for each order and there is an inventory holding cost i t per item per period (s t and i t can also vary with time if desired). The problem is how many units x t to order now to minimize the sum of setup cost and inventory cost. Let us denote inventory:
The total cost is given by the sum of setup costs, purchase order cost, stockout cost and inventory carrying cost: (,) = + [(,)] + (,) What changes with this approach is the computation of the optimal reorder point:
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