Drone-assisted delivery optimization: Balancing time and cost with multiple truck routes for efficient service

Conventional last-mile delivery logistical systems remain overburdened despite large-scale optimization. This paper explores the usage of drones to complement road-based last-mile delivery systems to ensure more time-cost efficiency. The work also extends the truck shipment routes to the case of real-time multiple routes. A bi-objective mixed integer linear program is introduced, accompanied by an exact solution methodology utilizing multi-choice conic goal programming. This approach guarantees the generation of properly efficient points and effectively addresses smaller-scale problems. For larger instances, a three-step iterative heuristic is proposed that generates good time and cost solutions in a reasonable amount of time. Exhaustive computational analysis and an illustrative case suggest that substantial savings in both time and cost can be achieved compared to traditional frameworks.