SPS Resources & Publications
Explore a curated collection of research papers, presentations, and essential materials on Stochastic Programming, designed to support learning and innovation in the field.
SIPLIB (Stochastic Integer Programming Library)
A library of test instances for stochastic integer programming problems.
https://www2.isye.gatech.edu/~sahmed/siplib/
Watson SPLIB (Stochastic Programming Library)
Stochastic programming instances from various sources.
https://github.com/vitaut-archive/splib/tree/master/watson
Random RHS Test Instances
A collection of random right-hand side test problems for stochastic integer programs.
https://users.wpi.edu/~atrapp/randomrhs_2013.htm
Test Problems – University of Florida
Benchmark problems from various engineering areas.
https://www.ise.ufl.edu/uryasev/research/testproblems/
Cornell SP Datasets
Stochastic programming test datasets from Cornell ORIE.
https://people.orie.cornell.edu/huseyin/research/sp_datasets/sp_datasets.html
POSTS (Portable Stochastic Programming Test Set)
Extendible (to arbitrary numbers of periods and scenarios) instances of general linear recourse problems.
https://users.iems.northwestern.edu/~jrbirge/html/dholmes/post.html
Sampling Methods for Stochastic Programming
Companion test problems from a empirical comparison paper.
SDDP.jl
A JuMP extension for Stochastic Dual Dynamic Programming.
https://github.com/odow/SDDP.jl
mpi-sppy
MPI-based Stochastic Programming in Python
https://github.com/Pyomo/mpi-sppy
cvxstoc
Disciplined convex stochastic programming
https://github.com/alnurali/cvxstoc
StructDualDynProg.jl
Implementation of SDDP using the StructJuMP modeling interface
https://github.com/JuliaStochOpt/StructDualDynProg.jl
BendersOptim
Benders decomposition to solve mixed integer linear programs, especially stochastic programs.
https://github.com/jiedxu/BendersOptim
DynamicProgramming.jl
A Julia package for Stochastic Dynamic Programming
https://github.com/odow/DynamicProgramming.jl
ROC++
Robust Optimization in C++
scengen
Tool for generating scenarios for stochastic optimization models.
https://github.com/loehndorf/scengen
scenred
Scenario reduction library for simplifying stochastic programs while preserving statistical structure.
Applications of stochastic programming: Achievements and questions (Dupačová, 2002)
Historical review as well as selected modelling issues of multistage stochastic programs with recourse.
https://www.sciencedirect.com/science/article/pii/S037722170200070X
Stochastic Programming in Transportation and Logistics (Powell and Topaloglu, 2003)
Survey of the use of stochastic programming in freight transportation.
https://www.sciencedirect.com/science/article/pii/S0927050703100096
Stochastic Programming Models (Ruszczyński and Shapiro, 2003)
Introduction into the modeling stochastic optimization problems.
https://www.sciencedirect.com/science/article/pii/S0927050703100011
Stochastic programming with integer variables (Schultz, 2003)
Introduction to the structural analysis of and algorithm design for stochastic integer programs.
https://link.springer.com/article/10.1007/s10107-003-0445-z
Stochastic programming approach to optimization under uncertainty (Shapiro, 2007)
Discussion of the computational complexity and risk averse approaches to two and multistage stochastic programming.
https://link.springer.com/article/10.1007/s10107-006-0090-4
A Tutorial on Stochastic Programming (Shapiro and Philpott, 2007)
Introduction into some of the basic ideas of stochastic programming.
Stochastic Programming Models in Energy (Wallace and Fleten, 2003)
Introduction to energy optimization models that explicitly deal with uncertainty.
https://www.sciencedirect.com/science/article/pii/S0927050703100102
John R. Birge and François V. Louveaux. Introduction to Stochastic Programming, 2nd Ed., Springer, 2011.
Peter Kall and Janos Mayer. Stochastic Linear Programming: Models, Theory, and Computation, International Series in Operations Research & Management Science, Vol. 80, Springer, New York, 2005.
Peter Kall and Stein W. Wallace. Stochastic Programming. Wiley, Chichester, 2003.
Alan J. King and Stein W. Wallace. Modeling with Stochastic Programming, Springer Series in Operations Research and Financial Engineering, Springer, New York, 2012.
Kurt Marti. Stochastic Optimization Methods, Springer, New York, 2005.
G.Ch. Pflug, Alois Pichler. Multistage Stochastic Programming, Springer Series in Operations Research and Financial Engineering, Springer, New York, 2014.
G. Ch. Pflug, W. Roemisch. Modeling, Measuring and Managing Risk, World Scientific, 2007.
Andras Prekopa. Stochastic Programming, Kluwer Academic Publishers, Dordrecht, 1995.
Andrzej Ruszczyński and Alexander Shapiro (eds.). Stochastic Programming, Handbooks in Operations Research and Management Science, Vol. 10, Elsevier, 2003.
Alexander Shapiro, Topics in Stochastic Programming, CORE Lecture Series, Universite Catholique de Louvain, 2011.
Alexander Shapiro, Darinka Dentcheva and Andrzej Ruszczyski. Lectures on Stochastic Programming: Modeling and Theory, 3rd Ed., SIAM, Philadelphia, 2021.
Wim S. van Ackooij and Welington L. de Oliveira. Methods of Nonsmooth Optimization in Stochastic Programming, Springer, 2025.
Stein W. Wallace and William T. Ziemba (eds.). Applications of Stochastic Programming, MPS-SIAM Book Series on Optimization 5, SIAM, Philadelphia, 2005.
Below is a list of some of the pioneers in our field: