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Optimal planning of Last-Mile Delivery in a Hybrid Transportation System

Alian Nezhadi, Shiva | 2025

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 58646 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Hassan Nayebi, Erfan
  7. Abstract:
  8. Last-mile delivery, as the final stage of the retail supply chain, accounts for more than 50% of logistics costs and, with the growth of e-commerce and home delivery, exerts increasing pressure on urban networks. Forecasts indicate that the demand for last-mile delivery services will grow by approximately 78% by 2030, a trend that will lead to increased freight transport, pollutant emissions, and traffic congestion. The traditional truck-based delivery method, which requires separate visits to each customer, not only exacerbates traffic but also faces the challenge of failed deliveries. Therefore, the development of innovative solutions for last-mile delivery is considered a strategic necessity. The concept of truck–robot collaborative delivery is among the most promising approaches for last-mile delivery in urban logistics and is technically feasible. In this model, the truck functions as a mobile hub, while robots cover the final segment of the route to customers. In this study, a model is presented for such a delivery system, demonstrating how the total delivery cost can be minimized given a fixed number of available robots. Solving this routing problem requires decisions regarding the truck route (a sequence of potential locations for deploying robots) and the assignment of each customer’s order to a location along the truck’s route (where a robot is dispatched for delivery). Based on the review of related literature, the problem is formulated as a Mixed Integer Linear Program (MILP) and is decomposed into truck routing and robot scheduling subproblems. Due to its complexity, metaheuristic algorithms—specifically Tabu Search with customized operators and General Variable Neighborhood Search (GVNS)—are employed to solve problem instances of the desired size. The results, compared with the traditional delivery model, indicate a consistent reduction of 77–82% in truck mileage and a 35–57% reduction in total delivery cost. Thus, truck–robot collaborative delivery represents an economical and efficient solution for the transformation of urban logistics
  9. Keywords:
  10. Last Mile Delivery ; Vehicle Routing Problem ; Autonomous Robot ; Meta Heuristic Algorithm ; Hybrid Truck–Robot Delivery ; Mobile Hub

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