Sharing Cuts under Aggregated Forecasts when Decomposing Multi-stage Stochastic Programs
Published in Operations Research Letters , 2013
Recommended citation: de Queiroz, A.R., Morton, D.P., (2013) Sharing Cuts under Aggregated Forecasts when Decomposing Multi-stage Stochastic Programs, Operations Research Letters, 41(3): 311-316 https://doi.org/10.1016/j.orl.2013.03.003
Sampling-based decomposition algorithms (SBDAs) solve multi-stage stochastic programs. SBDAs can approximately solve problem instances with many time stages when the stochastic program exhibits interstage dependence in its right-hand side parameters by appropriately sharing cuts. We extend previous methods for sharing cuts in SBDAs, establishing new results under a novel interaction between a class of interstage dependency models, and how they appear in the stochastic program.