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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  1. Escudero, Laureano F.; Monge, Juan F.; Rodríguez-Chía, Antonio M.: On pricing-based equilibrium for network expansion planning. A multi-period bilevel approach under uncertainty (2020)
  2. Kolomvos, George; Saharidis, Georgios K. D.: Accelerating techniques on nested decomposition (2017)
  3. Rebennack, Steffen: Combining sampling-based and scenario-based nested Benders decomposition methods: application to stochastic dual dynamic programming (2016)
  4. Vossen, Thomas W. M.; Wood, R. Kevin; Newman, Alexandra M.: Hierarchical benders decomposition for open-pit mine block sequencing (2016)
  5. Zhang, Weini; Rahimian, Hamed; Bayraksan, Güzin: Decomposition algorithms for risk-averse multistage stochastic programs with application to water allocation under uncertainty (2016)
  6. Fábián, Csaba I.; Wolf, Christian; Koberstein, Achim; Suhl, Leena: Risk-averse optimization in two-stage stochastic models: computational aspects and a study (2015)
  7. Lorenz, Ulf; Wolf, Jan: Solving multistage quantified linear optimization problems with the alpha-beta nested Benders decomposition (2015)
  8. Espinoza, Daniel; Moreno, Eduardo: A primal-dual aggregation algorithm for minimizing conditional value-at-risk in linear programs (2014)
  9. Wolf, Christian; Fábián, Csaba I.; Koberstein, Achim; Suhl, Leena: Applying oracles of on-demand accuracy in two-stage stochastic programming -- a computational study (2014)
  10. Wolf, Christian; Koberstein, Achim: Dynamic sequencing and cut consolidation for the parallel hybrid-cut nested L-shaped method (2013)
  11. Noyan, Nilay: Risk-averse two-stage stochastic programming with an application to disaster management (2012)
  12. Watson, Jean-Paul; Woodruff, David L.; Hart, William E.: PySP: modeling and solving stochastic programs in Python (2012)
  13. Zverovich, Victor; Fábián, Csaba I.; Ellison, Eldon F. D.; Mitra, Gautam: A computational study of a solver system for processing two-stage stochastic LPs with enhanced Benders decomposition (2012)
  14. Ederer, Thorsten; Lorenz, Ulf; Martin, Alexander; Wolf, Jan: Quantified linear programs: a computational study (2011)
  15. Mahlke, Debora: A scenario tree-based decomposition for solving multistage stochastic programs. With application in energy production. (2011)
  16. Rasekh, Lila; Desrosiers, Jacques: A two-level interior-point decomposition algorithm for multi-stage stochastic capacity planning and technology acquisition (2011)
  17. Chen, Lijian; Homem-De-Mello, Tito: Re-solving stochastic programming models for airline revenue management (2010)
  18. Liu, Xinwei; Toh, Kim-Chuan; Zhao, Gongyun: On the implementation of a log-barrier progressive hedging method for multistage stochastic programs (2010)
  19. Rasekh, Lila; Desrosiers, Jacques: Solving multi-stage stochastic in-house production and outsourcing planning by two-level decomposition (2010)
  20. Trukhanov, Svyatoslav; Ntaimo, Lewis; Schaefer, Andrew: Adaptive multicut aggregation for two-stage stochastic linear programs with recourse (2010)

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