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This paper considers the basic Economic Order Quantity model that allows stockouts and backordering. It assumes that the number of defectives produced by the manufacturing process is random rather than constant. Specifically, we assume that each lot contains a random proportion of defective units. Based on this scenario, we adjust the EOQ with planned(More)
This paper extends the results developed by Nasri, Paknejad, and Affisco [7] to the case of basic Economic Order Quantity model with random defective units and two types of shortage. In addition to the general relationships for the optimal values of policy variables, the paper also provides closed form expressions when proportion of defective items in a lot(More)
Typically, traditional inventory models operate under the assumption of perfect quality. In this paper we modify an inventory model with finite-range stochastic lead time to allow for a random number of defective units in a lot. However, there is an extra cost for holding the defective items in the lot for the period before it is returned to the supplier.(More)
This paper extends the results of a series of recent papers which focused on the analytical investigation of the economic trade-offs associated with investment decisions aimed at changing the parameters of yield distribution, and thereby improving process quality, in an EOQ model with planned shortages and random production yield. Production yield is(More)
We study the impact of the efforts aimed at reducing the lead-time variability in a quality-adjusted stochastic inventory model. We assume that each lot contains a random number of defective units. More specifically, a logarithmic investment function is used that allows investment to be made to reduce lead-time variability. Explicit results for the optimal(More)