articleLogisticsFeb 4, 2026GOLD OA

Sustainable and Safe Last-Mile Delivery: A Multi-Objective Truck–Drone Matheuristic

Toronto Metropolitan University · California State University, Fullerton · +2 more institutions

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Abstract

Background

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.

Methods

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

4
total citations
FWCI
168.33
Percentile
99%
References
0
Too recent for citation history.

Authors

4

Topics & keywords

Keywords
  • Software deployment
  • Truck
  • Drone
  • Convergence (economics)
  • Linear programming
  • Traffic congestion
  • Routing (electronic design automation)
  • Service (business)
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