Iranian Institute of Industrial Engineering Journal of Industrial and Systems Engineering 1735-8272 16 2 2024 04 01 Data-Driven Robust Optimization for Hub Location-Routing Problem under Uncertain Environment 26 50 210377 EN MirMohammad Musavi School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran 0009-0006-6995-7996 Ali Bozorgi-Amiri School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran 0000-0002-1180-9572 Journal Article 2023 09 21 This study addresses the Hub Location-Routing Problem (HLRP) in transportation networks, considering the inherent uncertainty in travel times between nodes. We employed a method centered on data-driven robust optimization, utilizing Support Vector Clustering (SVC) to form an uncertainty set grounded in empirical data. The proposed methodology is compared against traditional uncertainty sets, showcasing its superior performance in providing robust solutions. A comprehensive case study on a retail store's transportation network in Tehran is presented, demonstrating significant differences in hub locations, allocations, and vehicle routes between deterministic and robust models. The SVC-based model proves to be particularly effective, yielding substantially improved objective function values compared to polyhedral and box uncertainty sets. The study concludes by highlighting the practical significance of this research and suggesting future directions for advancing transportation network optimization under uncertainty. https://www.jise.ir/article_210377_bf44a7caef279c1eba0b9595db3dc0d9.pdf