Sustainable and Safe Last-Mile Delivery: A Multi-Objective Truck–Drone Matheuristic
Toronto Metropolitan University · California State University, Fullerton · +2 more institutions
Abstract
The rapid growth of e-commerce has intensified the need for last-mile delivery systems that can navigate urban congestion while minimizing environmental impact. Hybrid truck–drone networks offer a promising solution by combining heavy-duty ground transport with aerial flexibility; however, their deployment faces significant challenges in jointly managing operational risks, energy limits, and regulatory compliance.
This study proposes a hybrid matheuristic framework to solve this multi-objective problem, simultaneously minimizing transportation cost, service time, energy consumption, and operational risk. A two-phase approach combines a metaheuristic for initial truck routing with a Mixed-Integer Linear Programming (MILP) formulation for optimal drone assignment and scheduling. This decomposition strikes a balance between exact optimization and computational scalability.
Citation impact
- FWCI
- 168.33
- Percentile
- 99%
- References
- 0
Authors
4- AMArmin Mahmoodi
Toronto Metropolitan University
- MDMehdi DavoodiCorresponding
California State University, Fullerton, Decision Sciences (United States)
- SMSaid M. Easa
Toronto Metropolitan University
- SMSeyed Mojtaba Sajadi
Aston University
Topics & keywords
- Software deployment
- Truck
- Drone
- Convergence (economics)
- Linear programming
- Traffic congestion
- Routing (electronic design automation)
- Service (business)