Abstract
This paper investigates the problem of optimizing product recovery options within the reverse logistic context. A linear programming model is developed to find optimal allocation of returned products in different quality classes to certain recovery options. The objective is to maximize the profit. Qualities and quantities of returned products, demands, prices of the recovered products and costs for recovery are all considered in the model. The model is used to examine the effects of flexibility in product recovery allocation. Computation results show that flexible allocation between the returned products in different quality classes and the recovery options are beneficial.
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