Merging Green Vehicles and Crowdsourcing for Optimal Last-Mile Deliveries

This paper explores the optimization of last-mile delivery operations by leveraging both green vehicles and crowdsourcing strategies. The problem is modeled for a single depot, where Regular Drivers (RDs) and Occasional Drivers (ODs) collaborate to fulfill customer demands. RDs use traditional delivery vehicles, stationed near the depot, while ODs are individuals who transport goods as part of their routine travel between specified origins and destinations. The study considers the use of both petrol/diesel and electric vehicles by RDs and ODs, accommodating various vehicle capacities. The objective is to minimize the total cost of delivery, which includes transportation costs and penalties for unmet customer demands. The model aims to maximize the company's profit by optimizing vehicle routing, balancing the environmental impact of vehicle choices, and effectively utilizing crowdsourced drivers. We formulate the optimality conditions for the company and ODs, as well as equilibrium conditions for customers and derive the variational inequality models for each level of decision makers. The total variational inequality for the network is then determined, providing insights into how integrating green vehicles and crowdsourcing can enhance efficiency and sustainability in last-mile logistics.