Approximate dynamic programming for network recovery problems with stochastic demand
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DOI: 10.1016/j.tre.2021.102358
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- Timperio, Giuseppe & Kundu, Tanmoy & Klumpp, Matthias & de Souza, Robert & Loh, Xiu Hui & Goh, Kelvin, 2022. "Beneficiary-centric decision support framework for enhanced resource coordination in humanitarian logistics: A case study from ASEAN," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
- Souza Almeida, Luana & Goerlandt, Floris & Pelot, Ronald, 2022. "Trends and gaps in the literature of road network repair and restoration in the context of disaster response operations," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
- Kundu, Tanmoy & Sheu, Jiuh-Biing & Kuo, Hsin-Tsz, 2022. "Emergency logistics management—Review and propositions for future research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
- Liu, Kanglin & Zhang, Hengliang & Zhang, Zhi-Hai, 2021. "The efficiency, equity and effectiveness of location strategies in humanitarian logistics: A robust chance-constrained approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
- Hosseini, Yaser & Mohammadi, Reza Karami & Yang, Tony Y., 2024. "A comprehensive approach in post-earthquake blockage prediction of urban road network and emergency resilience optimization," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
- Nabavi, S.M. & Vahdani, Behnam & Nadjafi, B. Afshar & Adibi, M.A., 2022. "Synchronizing victim evacuation and debris removal: A data-driven robust prediction approach," European Journal of Operational Research, Elsevier, vol. 300(2), pages 689-712.
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Keywords
Network recovery problem; Stochastic networks; Demand uncertainty; Post-disaster response; Approximate dynamic programming;All these keywords.
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