MSLiP
MSLiP: A computer code for the multistage stochastic linear programming problem This paper describes an efficient implementation of a nested decomposition algorithm for the multistage stochastic linear programming problem. Many of the computational tricks developed for deterministic staircase problems are adapted to the stochastic setting and their effect on computation times is investigated. The computer code supports an arbitrary number of time periods and various types of random structures for the input data. Numerical results compare the performance of the algorithm to MINOS 5.0
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References in zbMATH (referenced in 105 articles , 1 standard article )
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Sorted by year (- Rebennack, Steffen: Combining sampling-based and scenario-based nested Benders decomposition methods: application to stochastic dual dynamic programming (2016)
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- Liu, Xinwei; Toh, Kim-Chuan; Zhao, Gongyun: On the implementation of a log-barrier progressive hedging method for multistage stochastic programs (2010)
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- Epe, Alexa; Küchler, Christian; Römisch, Werner; Vigerske, Stefan; Wagner, Hermann-Josef; Weber, Christoph; Woll, Oliver: Optimization of dispersed energy supply --- stochastic programming with recombining scenario trees (2009)
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