EVPI‐based importance sampling solution proceduresfor multistage stochastic linear programmeson parallel MIMD architectures
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DOI: 10.1023/A:1018956530304
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Cited by:
- Staino, Alessandro & Russo, Emilio, 2015. "A moment-matching method to generate arbitrage-free scenarios," European Journal of Operational Research, Elsevier, vol. 246(2), pages 619-630.
- Kostrova, Alisa & Britz, Wolfgang & Djanibekov, Utkur & Finger, Robert, 2016. "Monte-Carlo Simulation and Stochastic Programming in Real Options Valuation: the Case of Perennial Energy Crop Cultivation," Discussion Papers 250253, University of Bonn, Institute for Food and Resource Economics.
- 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.
- Michael Chen & Sanjay Mehrotra & Dávid Papp, 2015. "Scenario generation for stochastic optimization problems via the sparse grid method," Computational Optimization and Applications, Springer, vol. 62(3), pages 669-692, December.
- Pflug, Georg Ch., 2006. "A value-of-information approach to measuring risk in multi-period economic activity," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 695-715, February.
- Ekblom, J. & Blomvall, J., 2020. "Importance sampling in stochastic optimization: An application to intertemporal portfolio choice," European Journal of Operational Research, Elsevier, vol. 285(1), pages 106-119.
- Wolf, Christian & Koberstein, Achim, 2013. "Dynamic sequencing and cut consolidation for the parallel hybrid-cut nested L-shaped method," European Journal of Operational Research, Elsevier, vol. 230(1), pages 143-156.
- F. Wu & H. Li & L. Chu & D. Sculli & K. Gao, 2009. "An approach to the valuation and decision of ERP investment projects based on real options," Annals of Operations Research, Springer, vol. 168(1), pages 181-203, April.
- Yonghan Feng & Sarah Ryan, 2016. "Solution sensitivity-based scenario reduction for stochastic unit commitment," Computational Management Science, Springer, vol. 13(1), pages 29-62, January.
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