Stochastic Programming is a framework for modeling and solving problems of decision making under uncertainty. Stochastic Dynamic Programming, originally introduced by Richard Bellman in his seminal book Dynamic Programming, is a branch of Stochastic Programming that deals with multistage decision processes and takes a "functional equation" approach to the discovery of optimum policies.
jsdp provides a general purpose Java library for modeling and solving Stochastic Dynamic Programs. The library features a number of applications in maintenance, stochastic optimal control, and stochastic lot sizing; including the computation of optimal nonstationary (s,S) policy parameters, as discussed by Herbert Scarf in his seminal work the optimality of (s s) policies in the dynamic inventory problem.
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