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Risk aversion in multistage stochastic programming: A modeling and algorithmic perspective

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  1. Lorenzo Reus & Guillermo Alexander Sepúlveda-Hurtado, 2023. "Foreign exchange trading and management with the stochastic dual dynamic programming method," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-38, December.
  2. Fattahi, Mohammad & Keyvanshokooh, Esmaeil & Kannan, Devika & Govindan, Kannan, 2023. "Resource planning strategies for healthcare systems during a pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 192-206.
  3. Bäuerle, Nicole & Glauner, Alexander, 2022. "Markov decision processes with recursive risk measures," European Journal of Operational Research, Elsevier, vol. 296(3), pages 953-966.
  4. Zarei, Mohammadamin & Shams, Mohammad H. & Niaz, Haider & Won, Wangyun & Lee, Chul-Jin & Liu, J. Jay, 2022. "Risk-based multistage stochastic mixed-integer optimization for biofuel supply chain management under multiple uncertainties," Renewable Energy, Elsevier, vol. 200(C), pages 694-705.
  5. Xin, Linwei & Goldberg, David A., 2021. "Time (in)consistency of multistage distributionally robust inventory models with moment constraints," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1127-1141.
  6. Unai Aldasoro & María Merino & Gloria Pérez, 2019. "Time consistent expected mean-variance in multistage stochastic quadratic optimization: a model and a matheuristic," Annals of Operations Research, Springer, vol. 280(1), pages 151-187, September.
  7. Kraft, Emil & Russo, Marianna & Keles, Dogan & Bertsch, Valentin, 2023. "Stochastic optimization of trading strategies in sequential electricity markets," European Journal of Operational Research, Elsevier, vol. 308(1), pages 400-421.
  8. Wim Ackooij & Welington Oliveira & Yongjia Song, 2019. "On level regularization with normal solutions in decomposition methods for multistage stochastic programming problems," Computational Optimization and Applications, Springer, vol. 74(1), pages 1-42, September.
  9. Alonso-Ayuso, Antonio & Escudero, Laureano F. & Guignard, Monique & Weintraub, Andres, 2018. "Risk management for forestry planning under uncertainty in demand and prices," European Journal of Operational Research, Elsevier, vol. 267(3), pages 1051-1074.
  10. Alkhaleel, Basem A. & Liao, Haitao & Sullivan, Kelly M., 2022. "Risk and resilience-based optimal post-disruption restoration for critical infrastructures under uncertainty," European Journal of Operational Research, Elsevier, vol. 296(1), pages 174-202.
  11. Audrius Kabašinskas & Francesca Maggioni & Kristina Šutienė & Eimutis Valakevičius, 2019. "A multistage risk-averse stochastic programming model for personal savings accrual: the evidence from Lithuania," Annals of Operations Research, Springer, vol. 279(1), pages 43-70, August.
  12. Bushaj, Sabah & Büyüktahtakın, İ. Esra & Haight, Robert G., 2022. "Risk-averse multi-stage stochastic optimization for surveillance and operations planning of a forest insect infestation," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1094-1110.
  13. Laur, Arnaud & Nieto-Martin, Jesus & Bunn, Derek W. & Vicente-Pastor, Alejandro, 2020. "Optimal procurement of flexibility services within electricity distribution networks," European Journal of Operational Research, Elsevier, vol. 285(1), pages 34-47.
  14. Thuener Silva & Davi Valladão & Tito Homem-de-Mello, 2021. "A data-driven approach for a class of stochastic dynamic optimization problems," Computational Optimization and Applications, Springer, vol. 80(3), pages 687-729, December.
  15. Andre Luiz Diniz & Maria Elvira P. Maceira & Cesar Luis V. Vasconcellos & Debora Dias J. Penna, 2020. "A combined SDDP/Benders decomposition approach with a risk-averse surface concept for reservoir operation in long term power generation planning," Annals of Operations Research, Springer, vol. 292(2), pages 649-681, September.
  16. Mike G. Tsionas & Dionisis Philippas & Constantin Zopounidis, 2023. "Exploring Uncertainty, Sensitivity and Robust Solutions in Mathematical Programming Through Bayesian Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 205-227, June.
  17. Bakker, Hannah & Dunke, Fabian & Nickel, Stefan, 2020. "A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice," Omega, Elsevier, vol. 96(C).
  18. Laureano F. Escudero & María Araceli Garín & Celeste Pizarro & Aitziber Unzueta, 2018. "On efficient matheuristic algorithms for multi-period stochastic facility location-assignment problems," Computational Optimization and Applications, Springer, vol. 70(3), pages 865-888, July.
  19. Haodong Yu & Jie Sun & Yanjun Wang, 2021. "A time-consistent Benders decomposition method for multistage distributionally robust stochastic optimization with a scenario tree structure," Computational Optimization and Applications, Springer, vol. 79(1), pages 67-99, May.
  20. Kallio, Markku & Halme, Merja & Dehghan Hardoroudi, Nasim & Aspara, Jaakko, 2022. "Transparent structured products for retail investors," European Journal of Operational Research, Elsevier, vol. 302(2), pages 752-767.
  21. Fernández, Elena & Hinojosa, Yolanda & Puerto, Justo & Saldanha-da-Gama, Francisco, 2019. "New algorithmic framework for conditional value at risk: Application to stochastic fixed-charge transportation," European Journal of Operational Research, Elsevier, vol. 277(1), pages 215-226.
  22. İ. Esra Büyüktahtakın, 2022. "Stage-t scenario dominance for risk-averse multi-stage stochastic mixed-integer programs," Annals of Operations Research, Springer, vol. 309(1), pages 1-35, February.
  23. Bernardo K. Pagnoncelli & Felipe del Canto & Arturo Cifuentes, 2021. "The effect of regularization in portfolio selection problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 156-176, April.
  24. Liu, Jia & Chen, Zhiping, 2018. "Time consistent multi-period robust risk measures and portfolio selection models with regime-switching," European Journal of Operational Research, Elsevier, vol. 268(1), pages 373-385.
  25. Laureano F. Escudero & Juan F. Monge, 2018. "On capacity expansion planning under strategic and operational uncertainties based on stochastic dominance risk averse management," Computational Management Science, Springer, vol. 15(3), pages 479-500, October.
  26. Escudero, Laureano F. & Garín, M. Araceli & Monge, Juan F. & Unzueta, Aitziber, 2020. "Some matheuristic algorithms for multistage stochastic optimization models with endogenous uncertainty and risk management," European Journal of Operational Research, Elsevier, vol. 285(3), pages 988-1001.
  27. Yin, Xuecheng & Büyüktahtakın, İ. Esra & Patel, Bhumi P., 2023. "COVID-19: Data-Driven optimal allocation of ventilator supply under uncertainty and risk," European Journal of Operational Research, Elsevier, vol. 304(1), pages 255-275.
  28. W. Ackooij & X. Warin, 2020. "On conditional cuts for stochastic dual dynamic programming," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 8(2), pages 173-199, June.
  29. Nicole Bauerle & Alexander Glauner, 2020. "Markov Decision Processes with Recursive Risk Measures," Papers 2010.07220, arXiv.org.
  30. Baptista, Susana & Barbosa-Póvoa, Ana Paula & Escudero, Laureano F. & Gomes, Maria Isabel & Pizarro, Celeste, 2019. "On risk management of a two-stage stochastic mixed 0–1 model for the closed-loop supply chain design problem," European Journal of Operational Research, Elsevier, vol. 274(1), pages 91-107.
  31. Theodore T. Allen & Zhenhuan Sui & Nathan L. Parker, 2017. "Timely Decision Analysis Enabled by Efficient Social Media Modeling," Decision Analysis, INFORMS, vol. 14(4), pages 250-260, December.
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