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Piecewise linear approximations for the static-dynamic uncertainty strategy in stochastic lot-sizing
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===================================================================== pwlf-milp: Piecewise linear approximations for the static-dynamic uncertainty strategy in stochastic lot-sizing ===================================================================== http://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 http://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 http://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.
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