MSc Thesis Defense: Mohammadjavad Nosrati Zegoloujeh, TRUCK–DRONE DELIVERY ROUTING PROBLEM UNDER WEATHER UNCERTAINTY, Date & Time: 21 July, 2026 – 1:00 PM, Place: FENS L062

TRUCK–DRONE DELIVERY ROUTING PROBLEM UNDER WEATHER UNCERTAINTY

Mohammadjavad Nosrati Zegoloujeh

Industrial Engineering, MSc Thesis, 2026

Thesis Jury

     Asst. Prof. İhsan Sadati (Thesis Advisor)

  Prof. Erhun Kundakcıoğlu

Asst. Prof. Sina Rastani

Date & Time: 21st of July, 2026 – 1:00 PM

Place: FENS L062

Keywords : Truck–Drone Routing Problem, Wind Speed Uncertainty, Variable Neighborhood

Search, Last-Mile Delivery

Abstract

The increasing demand for efficient and sustainable last-mile delivery has encouraged the integration of trucks and unmanned aerial vehicles (UAVs) in logistics operations. Although UAVs can improve delivery speed, accessibility, and environmental sustainability, their performance is significantly affected by weather conditions, particularly wind speed. This thesis investigates the truck–drone delivery vehicle routing problem with weather uncertainty (TDDVRP–WU), in which each truck operates in coordination with a single UAV under uncertain wind conditions. Due to the NP-hard nature of the problem, a Probabilistic Variable Neighborhood Search (P-VNS) algorithm is developed to efficiently obtain high-quality solutions for the TDDVRP–WU. Computational experiments demonstrate that the proposed approach effectively generates robust truck–drone delivery plans while accounting for wind uncertainty. The results highlight the importance of incorporating weather-related factors into routing decisions and demonstrate the potential of the proposed methodology for improving the reliability and efficiency of last-mile delivery operations.