Abstract
With the recent surge of industrialisation and advancement of technologies, supply chain management has been widely permeated by the practice of reverse logistics and zero-waste circular economy. Literature on these topics has covered several reverse logistics optimisation problems; however, the area of the vehicle routing problem has only been explored to a limited extent, notwithstanding the costs associated with route planning under bi-directional pathways. E-commerce logistics is not well-represented in previous works; and of such existing studies, no model has quantified the performance of the routing plan on the basis of all three sustainability measures. In this light, the objective of the present paper is to model the forward-reverse logistics network of e-commerce organisations and determine optimal routing plans based on economic, environmental, and social performance measures. To fulfil this, a mixed-integer linear programming problem (MILP) integrating the minimisation of three types of costs, namely (1) operational costs, (2) carbon emissions, and (3) highest energy use of vehicle drivers, was formulated and then evaluated using a hypothetical case study. The findings indicated that the proposed model was successful in optimising all three aspects of sustainability, with a weighted average deviation of a minimal 9.02 % from the potential of each objective. Under the optimal routing scheme, all vehicles are deployed and assigned paths such that they leverage the unique benefits of the vehicles in sustainable terms.