Vehicle Routing Problem with Stochastic and Mobile Delivery Location

Recent developments in e-commerce have led to a significant increase in online purchases, propelling the retail segment to constantly search for innovative solutions to fill research gaps. One of the main challenges in last-mile delivery is presence of customers at the delivery locations. We study a stochastic variant of the vehicle routing problem with mobile and stochastic delivery locations for a limited number of customers to reduce transportation costs. In this study, some customers can choose different delivery locations during their daily commutes with a probability of presence at each location. We propose a two-stage stochastic model and assess its effectiveness by optimizing two sets of relatively small problems using the Gurobi optimization solver. The results show 8–15% reduction in the total travel cost while eliminating delivery failures.