Stochastic Optimisation Approaches for Truck-Drone Tandems in Humanitarian Applications

: (Alternative Format Thesis)

Abstract

This thesis comprises three papers on multimodal delivery systems involving drones in humanitarian and healthcare logistics, with the main applications in humanitarian contexts. The first paper presents a systematic literature review on multimodal delivery involving drones in humanitarian and healthcare logistics. It provides a comprehensive analysis of this growing field, identifies key trends, and highlights gaps such as the treatment of uncertainty and the design of collaboration structures.

The second and third papers address stochastic network design problems for relief distribution involving trucks and drones. Both papers formulate stochastic location–routing models that account for disaster-related uncertainties, particularly variable travel times on disrupted road networks, and propose tailored heuristic solution approaches. The second paper investigates parallel operations, where trucks and drones depart independently from depots, while the third examines synchronised operations, where trucks and drones coordinate launches and retrievals. Both studies evaluate the integration of uncertainty into the decision-making process and the role of drones alongside traditional ground vehicles, demonstrating their potential to improve response times in the aftermath of disasters.

Date of Award	20 May 2026
Original language	English
Awarding Institution	University of Bath
Supervisor	Melih Celik (Supervisor), Omid Maghazei (Supervisor) & Ece Sanci (Supervisor)