SDDP.jl : A Julia Package for Stochastic Dual Dynamic Programming

Oscar Dowson · Lea Kapelevich

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Risk and Portfolio Optimization Advanced Control Systems Optimization Advanced Optimization Algorithms Research

Abstract

We present SDDP.jl, an open-source library for solving multistage stochastic programming problems using the stochastic dual dynamic programming algorithm. SDDP.jl is built on JuMP, an algebraic modeling language in Julia. JuMP provides SDDP.jl with a solver-agnostic, user-friendly interface. In addition, we leverage unique features of Julia, such as multiple dispatch, to provide an extensible framework for practitioners to build on our work. SDDP.jl is well tested, and accessible documentation is available at https://github.com/odow/SDDP.jl .

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References

1999Coherent Measures of Risk 1985Decomposition and Partitioning Methods for Multistage Stochastic Linear Programs 2010Analysis of stochastic dual dynamic programming method 2018Stochastic dual dynamic integer programming 2008On the convergence of stochastic dual dynamic programming and related methods 2011Dynamic sampling algorithms for multi-stage stochastic programs with risk aversion 2014On the Convergence of Decomposition Methods for Multistage Stochastic Convex Programs 2013On Solving Multistage Stochastic Programs with Coherent Risk Measures

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