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# 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} }

- Published 2012 in Math. Program. Comput.
DOI:10.1007/s12532-012-0036-1

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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