Due to the emergence of e-commerce and the\nproliferation of liberal return policies, product returns\nhave become daily routines for many companies.\nConsidering the significant impact of product returns on\nthe company�s bottom line, a growing number of\ncompanies have attempted to streamline the reverse\nlogistics process. Products are usually returned to initial\ncollection points (ICPs) in small quantities and thus\nincrease the unit shipping cost due to lack of freight\ndiscount opportunities. One way to address this issue is\nto aggregate the returned products into a larger\nshipment. However, such aggregation increases the\nholding time at the ICP, which in turn increases the\ninventory carrying costs. Considering this logistics\ndilemma, the main objectives of this research are to\nminimize the total cost by determining the optimal\nlocation and collection period of holding time of ICPs;\ndetermining the optimal location of a centralized return\ncentre; transforming the nonlinear objective function of\nthe proposed model formulation by Min et al. (2006a) into\na linear form; and conducting a sensitivity analysis to the\nmodel solutions according to varying parameters such as\nshipping volume. Existing models and solution\nprocedures are too complicated to solve real-world\nproblems. Through a series of computational\nexperiments, we discovered that the linearization model\nobtained the optimal solution at a fraction of the time\nused by the traditional nonlinear model and solution\nprocedure, as well as the ability to handle up to 150\ncustomers as compared to 30 in the conventional\nnonlinear model. As such, the proposed linear model is\nmore suitable for actual industry applications than the\nexisting models.
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