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http://hdl.handle.net/11375/32082Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | Hassini, Elkafi | - |
| dc.contributor.author | Pushkar, Shamik | - |
| dc.date.accessioned | 2025-07-31T20:49:02Z | - |
| dc.date.available | 2025-07-31T20:49:02Z | - |
| dc.date.issued | 2025 | - |
| dc.identifier.uri | http://hdl.handle.net/11375/32082 | - |
| dc.description.abstract | The integration of drones into last-mile delivery systems has garnered significant attention across sectors such as e-commerce, healthcare, and emergency logistics. Despite technological advancements and industry investment, widespread adoption remains limited due to regulatory, financial, and operational challenges. This thesis investigates the feasibility and efficiency of drone-assisted delivery under real-world constraints, with a particular focus on regulatory frameworks. Three mathematical models are developed. The first evaluates the impact of no-fly zones and flight distance restrictions on coordinated truck-drone delivery. The second introduces a hybrid logistics model incorporating droneports to facilitate delivery in urban areas with zoning laws. The third addresses a rural healthcare application, proposing a synchronized delivery and scheduling model for livestock vaccine administration, balancing workload among veterinarians. Each model is formulated as a Mixed Integer Linear Program (MILP), with computational experiments validating their performance. Heuristic and matheuristic algorithms are proposed to solve large-scale instances. Results demonstrate that while drones can enhance delivery efficiency and equity, their benefits are significantly influenced by regulatory severity and operational design. | en_US |
| dc.language.iso | en | en_US |
| dc.subject | delivery, drones, regulations, optimization, accessibility | en_US |
| dc.title | Optimizing Drone-Enabled Logistics: Mathematical Models for Regulatory-Constrained Delivery in Urban and Rural Environments | en_US |
| dc.title.alternative | Optimizing Drone-Enabled Logistics | en_US |
| dc.type | Thesis | en_US |
| dc.contributor.department | Business | en_US |
| dc.description.degreetype | Thesis | en_US |
| dc.description.degree | Doctor of Management (DMgt) | en_US |
| dc.description.layabstract | Drones have emerged as a promising solution for improving delivery services, especially in areas where traditional transportation faces challenges. However, despite growing interest from both industry and academia, real-world adoption of drone delivery remains limited. This is largely due to strict government regulations, limited flight range, and the need for safe and efficient coordination with existing delivery systems. This thesis explores how drones can be effectively integrated into delivery networks in both urban and rural settings. It presents three mathematical models that address key challenges in drone deployment. The first model examines how regulations—such as no-fly zones and flight distance limits—affect the feasibility and cost of drone delivery. The second model focuses on urban areas where drones are restricted in densely populated zones but allowed in less populated regions. It introduces the concept of "droneports" as hubs where drones can be launched and retrieved safely. The third model tackles a real-world problem in rural veterinary care, where drones deliver vaccines and veterinarians travel separately to administer them. This model aims to reduce stress and workload among rural veterinarians by balancing their schedules more fairly. Through detailed simulations and optimization techniques, the research shows that drones can significantly improve delivery efficiency and service equity—provided that regulatory and operational constraints are carefully managed. | en_US |
| Appears in Collections: | Open Access Dissertations and Theses | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| pushkar_shamik_2025July_PHD.pdf | 1.54 MB | Adobe PDF | View/Open |
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