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pwlf-milp: Piecewise linear approximations for the static-dynamic 
           uncertainty strategy in stochastic lot-sizing
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https://gwr3n.github.io/pwlf-milp/

pwlf-milp provides an implementation of the techniques presented in 

R. Rossi, O. A. Kilic, S. A. Tarim, 
"Piecewise linear approximations for the static-dynamic uncertainty strategy in stochastic lot-sizing", 
OMEGA - the International Journal of Management Science, Elsevier, Vol. 50:126-140, 2015
https://dx.doi.org/10.1016/j.omega.2014.08.003

R. Rossi, S. A. Tarim, B. Hnich and S. Prestwich, 
"Piecewise linear lower and upper bounds for the standard normal first order loss function", 
Applied Mathematics and Computation, Elsevier, Vol. 231:489-502, 2014
https://dx.doi.org/10.1016/j.amc.2014.01.019

R. Rossi, E.M.T. Hendrix, 
"Computing linearisation parameters of arbitrarily distributed first order loss functions", 
in Proceedings of MAGO'14, XII Global Optimization Workshop (GOW)
https://gwr3n.github.io/chapters/Rossi_et_al_MAGO_2014_2.pdf 
 
to piecewise linearise arbitrary loss functions and compute near-optimal
control policy parameters for the static-dynamic uncertainty strategy in stochastic lot-sizing. 

This library requires IBM ILOG CPLEX 12.10, which can be obtained at the following address  
https://www.ibm.com/support/pages/downloading-ibm-ilog-cplex-optimization-studio-v12100

pwlf-milp is maintained by Roberto Rossi, Full Professor at the University of Edinburgh.