| Summary: | 碩士 === 淡江大學 === 管理科學研究所碩士班 === 99 === Deteriorating items in the nature can be divided into "instantaneous deterioration" and "non-instantaneous deterioration". Instantaneous deteriorating is the item purchased immediately began to degenerate and can’t be retain the original quality. Non-instantaneous deterioration is not immediately degraded after the purchase and it still can maintain the original quality for some time then began to degenerate. This type of item is referred to as "non-instantaneous deteriorating items" and it is also the main items of the inventory we discuss in this paper.
The demand rate of item is changing. Consumers usually attracted by the large quantities of goods on shelves and stimulate purchase intention. And some items are due to short life cycle or homogeneous lead the demand rate of some items decrease rapidly. For example, 3C products , therefore, assuming the demand rate is fixed consistent does not meet current various market environment.
On the other hand, inventory could be the backlog of capital. Inventory models discussed previously ware that sell out of goods then reorder another lots. But for non-instantaneous deteriorating items, before selling out of goods we sell the goods of a lower price then reorder another lots. For retailers, it may be more beneficial for them. Therefore, in this paper, we relax the terminal condition of zero of inventory level at the end of cycle. Then we consider there are still some goods at the end of cycle sold with a lower price and allow shortages, backlogging in the model.
Summary, this paper is to explore the non-instantaneous deteriorating items and relax the terminal condition of the inventory system. In Chapter 2 we assume a demand rate and inventory levels related and we allow the shortages and the partial backorder, backorder rate is fixed. In Chapter 3 we consider the demand rate is a decreasing exponential function of time and don’t allow out of stock. Two chapters of the models in order to achieve the maximum total profit per unit time as the goal, and then use mathematical methods to get the optimal solution. Then we example illustrates both the value and sensitivity analysis of parameters and show the steps of solution. Finally, concluding remarks are made in Chapter 4 and future research directions are proposed.
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