Date of Award
2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Civil and Environmental Engineering
Committee Chair
Michael D. Anderson
Committee Member
Sampson Gholston
Committee Member
Avinash Unnikrishnan
Committee Member
Yooseob Song
Research Advisor
Rui Ma
Subject(s)
Food delivery services, Food delivery services--Transportation, Food delivery services--Management, Food delivery services--Technological innovations
Abstract
The on-demand meal delivery sector has experienced significant transformation, reshaping consumer dining habits and operational practices in the food delivery industry. This dissertation explores the changing landscape of on-demand meal delivery services through two interrelated topics, namely Modeling On-demand Meal Delivery in a Link-Node Based stochastic User Equilibrium with certain demand and Modeling On-demand Meal Delivery with different vehicle modes and uncertain demand, aiming to address the evolving challenges and opportunities in this dynamic industry. The rest of this dissertation is composed of two parts. The first part addresses the integration of internal restaurant couriers and third-party platform couriers to improve delivery efficiency and meet customer demands. A comprehensive on-demand meal delivery model is presented, which combines these two delivery methods. The model focuses on optimizing delivery operations by identifying strategies for hiring and managing couriers, minimizing travel costs, and maximizing customer satisfaction. It also considers constraints such as road network topology, time-dependent demand patterns, and restaurant strategies, offering a robust and adaptable solution for meal delivery operations. By integrating traffic information and utilizing the Stochastic User Equilibrium model to predict route choices, the model provides actionable insights for restaurants to enhance their delivery operations. The second part addresses the intricate challenges of on-demand meal delivery operations, including dynamic routing, multiple delivery courier modes, demand uncertainty, and bundling in an integrated delivery system. An advanced simulation optimization model is developed to incorporate all of these challenges and find the most efficient solution for them. This part further develops the envisions on the stochastic nature of real-world demand scenarios. By dynamically assigning delivery tasks to the most suitable courier based on factors such as workload, load capacity, and fuel consumption, the model optimizes delivery routes and resource utilization, ensuring efficient and effective service. Furthermore, the model has the potential to consider multiple delivery modes, such as electric vehicles, drones, conventional vehicles, bikes, and other types of courier modes, to improve operational efficiency, reduce costs, and minimize environmental impact. By integrating these innovative technologies into the model, a more sustainable and customer-centric approach to food delivery is promoted. Additionally, the model investigates the advantages of bundling orders and implementing an integrated delivery system for multiple restaurants. This strategy simplifies delivery logistics, improves coordination, and guarantees a consistent and high-quality service. Through rigorous analysis and the application of relevant models, this dissertation provides valuable insights and practical solutions for businesses in the food delivery industry to adapt to evolving market demands and maintain a competitive edge.
Recommended Citation
Noormohamadzade, Zohre, "Modeling on-demand meal delivery with multi-modal couriers: considering both certain and uncertain orders" (2024). Dissertations. 408.
https://louis.uah.edu/uah-dissertations/408