2021/11/30 by Zhuolin Wang, Keyou You, Wang, Zhuolin +5
Business, Management and Accounting · Engineering · #FOS: Electrical engineering #FOS: Mathematics #Facility Location and Emergency Management #Optimization and Control (math.OC) #Optimization and Mathematical Programming #Systems and Control (eess.SY) #Vehicle Routing Optimization Methods #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2111.15057
openalex publication_date 2021/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The key of the post-disaster humanitarian logistics (PD-HL) is to build a good facility location and capacity planning (FLCP) model for delivering relief supplies to affected areas in time. To fully exploit the historical PD data, this paper adopts the data-driven distributionally robust (DR) approach and proposes a novel multi-period FLCP model under the ∞-Wasserstein joint chance constraints (MFLCP-W). Specifically, we sequentially decide locations from a candidate set to build facilities with supply capacities, which are expanded if more economical, and use a finite number of historical demand samples in chance constraints to ensure a high probability of on-time delivery. To solve the MFLCP-W model, we equivalently reformulate it as a mixed integer second-order cone program and then solve it by designing an effective outer approximation algorithm with two tailored valid cuts. Finally, a case study under hurricane threats shows that MFLCP-W outperforms its counterparts in the terms of the cost and service quality, and that our algorithm converges significantly faster than the commercial solver CPLEX 12.8 with a better optimality gap.