A Model for Vehicle Routing Problem under Returns and Emission Consideration in B2C E-Commerce Logistics

Purpose: With the widespread use of the Internet, electronic commerce allows customers to purchase products from the virtual stores of businesses instead of physical stores. This study addressed a mixed-integer linear programming model for a vehicle routing problem under returns and emission considerations in B2C e-commerce logistics. Methodology: This study proposes a mathematical model to solve a variant of the vehicle routing problem. The objective is to minimize the fuel consumption cost, penalty cost for unmet demand of returned items, and fixed cost for operating a vehicle. A clustering-based solution algorithm has been introduced to solve large-sized instances within reasonable solution times. Findings: The numerical analysis for the base case shows that the suggested model can assist decision-makers in coordinating forward distribution and reverse collection decisions within the context of sustainable e-commerce logistics. The result of the adjusted model for minimizing emission shows that a reduction of nearly 17% in total emission amount can be achieved, however, the adjusted model postpones all demand for the collection of returned items. Furthermore, the cluster-based solution approach causes a considerable decrease in solution time while providing promising solutions. Originality: This study represents a contribution to the existing literature on the subject by considering: i) emission to determine effects on the vehicle routing problem, ii) the postponement of the collection of returned items due to the limited delivery time, iii) proposing the clustering-based solution approach to tackle with larger-sized problems.