| Summary: | 碩士 === 中原大學 === 工業與系統工程研究所 === 105 === Classical economic production quantity (EPQ) models usually assume all the items will remain in perfect condition. However, in real life some items will deteriorate over time. Deterioration is defined as damage, decay, obsolescence, and loss of value in a product along time. That is why deterioration needs to be considering when developing EPQ model. Many literatures assume that shortages are not permitted to occur. Nevertheless, in many practical situations, stock out is unavoidable due to various uncertainties. Therefore, the occurrence of shortages in inventory is a natural phenomenon. But only a few inventory models for deteriorating item with considering allowable shortages have been found in the literature. Due to this condition, this research study inventory model dealing with deteriorating item and allowing shortage.
In this research, three production inventory models are developed. The first model presents an economic production period (EPP) model with shortage without deteriorating item. In this model, we get optimal solution of total cost by search the optimal cycle length. The second model gives an EPP model for deteriorating item with shortage. This model find the optimal solution of total cost without using series approximation to simplify and neglecting second or higher order of θ term in the deteriorate function. The third model shows an EPP model for multi-deteriorating items with shortage. Furthermore, we develop this model considering a limited storage capacity for item and a limited budget production.
In this study, we develop an EPP inventory model of deteriorating items for multi-items with shortage. The main objective of this research is to minimize the total cost. Distribution of the deterioration item follows the exponential distribution. The optimum inventory cycle and the economic production period are decision variables. Since these mathematical models are complex, their closed form solutions cannot be derived. We use the simple search method using Maple 15 software to solve the models.
We provide the numerical example for each model to illustrate the theorems. The effects of key parameters changes to production up time and total cost demonstrated by presenting sensitivity analysis.
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