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Bi-objective Vehicle Routing Problem with Roaming Delivery Locations under Travel Time Uncertainty

Akhlaghi Feiz Asar, Roozmehr | 2025

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 58580 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Akbari Jokar, Mohammad Reza
  7. Abstract:
  8. The last-mile delivery stage has emerged as one of the major challenges in modern supply chains, accounting for a significant portion of logistics costs. This study investigates the Vehicle Routing Problem with Roaming Delivery Locations (VRPRDL) under travel-time uncertainty. In this problem, each customer may specify multiple possible delivery locations within different time windows, and the objective is to determine optimal routes for a fleet of vehicles while selecting the best delivery location for each customer. The main contribution of this research is the development of a bi-objective mathematical model that simultaneously minimizes operational costs and maximizes customer satisfaction. Moreover, for the first time in this class of routing problems, a budget-based robust optimization approach is adopted to model travel-time uncertainty. To solve the proposed model, two well-known multi-objective metaheuristic algorithms, NSGA-II and SPEA2, are applied. Numerical results indicate that both algorithms are capable of generating high-quality solutions close to the Pareto front within a reasonable computational time. The comparative analysis demonstrates that while SPEA2 achieves faster convergence, NSGA-II shows superior scalability and delivers better performance on larger-scale instances. Furthermore, comparing the robust and deterministic models reveals that the robust model provides more reliable and stable performance when dealing with uncertainty. This research can serve as a practical foundation for decision-making in real-world distribution systems, particularly in environments where both operational efficiency and customer satisfaction are essential and data uncertainty exists
  9. Keywords:
  10. Vehicle Routing Problem ; Roaming Delivery Locations ; Robust Optimization ; Multiobjective Optimization ; Customer Satisfaction ; Travel Time Uncertainty

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