Applying oracles of on-demand accuracy in two-stage stochastic programming  A computational study
We devise variants of the L-shaped method using the concept of on-demand accuracy (ODA). In many of the iterations only an approximate cut is added to the master problem. These cuts do not require the solution of second-stage subproblems. ODA reduces average solution time by 55% on 105 problems. ODA combined with regularization reduces average solution time by 79%.
stochastic programming two-stage problems decomposition bundle methods