Software for Data-Based Stochastic Programming Using Estimation

We describe software for stochastic programming that uses only sampled data to obtain both a consistent sample-average solution and a consistent estimate of confidence intervals for the optimality gap using bootstrap and bagging. The underlying distribution whence the samples come is not required.

Automated summary

This software utilizes sampled data to obtain a consistent sample-average solution and estimate confidence intervals for the optimality gap using bootstrap and bagging, without the need for considering the underlying distribution of the samples.