Abstract
Due to the emergence of e-commerce and the proliferation of liberal return policies, product returns have become daily routines for many companies. Considering the significant impact of product returns on the company's bottom line, a growing number of companies have attempted to streamline the reverse logistics process. Products are usually returned to initial collection points (ICPs) in small quantities and thus increase the unit shipping cost due to lack of freight discount opportunities. One way to address this issue is to aggregate the returned products into a larger shipment. However, such aggregation increases the holding time at the ICP, which in turn increases the inventory carrying costs. Considering this logistics dilemma, the main objectives of this research are to minimize the total cost by determining the optimal location and collection period of holding time of ICPs; determining the optimal location of a centralized return centre; transforming the nonlinear objective function of the proposed model formulation by Min et al. (2006a) into a linear form; and conducting a sensitivity analysis to the model solutions according to varying parameters such as shipping volume. Existing models and solution procedures are too complicated to solve real-world problems. Through a series of computational experiments, we discovered that the linearization model obtained the optimal solution at a fraction of the time used by the traditional nonlinear model and solution procedure, as well as the ability to handle up to 150 customers as compared to 30 in the conventional nonlinear model. As such, the proposed linear model is more suitable for actual industry applications than the existing models.
Highlights
Returned products come in all different sizes, shapes, and conditions
One way to address this issue is to aggregate the returned products into a larger shipment. Such aggregation increases the holding time at the initial collection points (ICPs), which in turn increases the inventory carrying costs. Considering this logistics dilemma, the main objectives of this research are to: (1) minimize the total cost by determining the optimal location of ICPs and direct customers to designated ICPs; determining the optimal collection period of holding time at the ICP; and determining the optimal location of a centralized return centre (CRC); and (2) to transform the nonlinear objective function of the proposed model formulation into a linear form that significantly eases the computational complexity; and (3) conduct a sensitivity analysis to the model solutions according to varying parameters such as shipping volume
Prior to developing a model that built upon the nonlinear-mixed integer program (MIP) proposed by Min et al (2006a) and transforming it into a linear form with the expanded variables and constraints, we made the following assumptions: (1) the possibility of direct shipment from customers to a centralized return centre is ruled out due to a small volume of individualized returns; (2) the transportation cost between customers and their ICPs is negligible given the short distances between the two parties; (3) the location/allocation plan covers a planning horizon in which customer demand patterns and transportation infrastructure remain stable without dramatic changes; (4) an ICP has adequate capacity to hold returned products during the collection period; (5) all customer locations are known and fixed a priori
Summary
Returned products come in all different sizes, shapes, and conditions. Many of them are received damaged, without original packages, and mixed up with other products. It was found that product returns cost businesses more than $100 billion a year and caused an average profit loss of 3.8% (Petersen and Kumar, 2010). In 2011 alone, for example, product returns cost U.S consumer electronics retailers and manufacturers nearly $17 billion: an increase of 21% since 2007. One way to address this issue is to aggregate the returned products into a larger shipment Such aggregation increases the holding time at the ICP, which in turn increases the inventory carrying costs. Considering this logistics dilemma, the main objectives of this research are to: (1) minimize the total cost by determining the optimal location of ICPs and direct customers to designated ICPs; determining the optimal collection period of holding time at the ICP; and determining the optimal location of a centralized return centre (CRC); and (2) to transform the nonlinear objective function of the proposed model formulation into a linear form that significantly eases the computational complexity; and (3) conduct a sensitivity analysis to the model solutions according to varying parameters such as shipping volume
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