PySP: modeling and solving stochastic programs in Python

@article{Watson2012PySPMA,
  title={PySP: modeling and solving stochastic programs in Python},
  author={Jean-Paul Watson and David L. Woodruff and William E. Hart},
  journal={Math. Program. Comput.},
  year={2012},
  volume={4},
  pages={109-149}
}
Although stochastic programming is a powerful tool for modeling decisionmaking under uncertainty, various impediments have historically prevented its widespread use. One key factor involves the ability of non-specialists to easily express stochastic programming problems as extensions of deterministic models, which are often formulated first. A second key factor relates to the difficulty of solving stochastic programming models, particularly the general mixed-integer, multi-stage case. Intricate… CONTINUE READING
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