SDDP.jl: A Julia Package for Stochastic Dual Dynamic Programming-Reference-Cited by-同舟云学术

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

Published:2021-01 Issue:1 Volume:33 Page:27-33
ISSN:1091-9856
Container-title:INFORMS Journal on Computing
language:en
Short-container-title:INFORMS Journal on Computing

Author:

Dowson Oscar¹^ORCID,Kapelevich Lea²

Affiliation:

1. Department of Industrial Engineering and Management Sciences, McCormick School of Engineering, Northwestern University, Evanston, Illinois 60208;

2. Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139

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 .

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

General Engineering

Reference27 articles.

1. Coherent Measures of Risk

2. Regularized Decomposition of High-Dimensional Multistage Stochastic Programs with Markov Uncertainty

3. Julia: A Fresh Approach to Numerical Computing

4. Decomposition and Partitioning Methods for Multistage Stochastic Linear Programs

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