A JuMP extension for Stochastic Dual Dynamic Programming
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Updated
Nov 7, 2024 - Julia
A JuMP extension for Stochastic Dual Dynamic Programming
Julia package for formulating and analyzing stochastic recourse models.
DecisionProgramming.jl is a Julia package for solving multi-stage decision problems under uncertainty, modeled using influence diagrams. Internally, it relies on mathematical optimization. Decision models can be embedded within other optimization models.
Data-driven decision making under uncertainty using matrices
Benders decomposition to solve mixed integer linear programming, especially stochastic programming in seconds!
Automatic optimal sequential investment decisions. Forecasts made using advanced stochastic processes with Monte Carlo simulation. Dependency is handled with vine copulas.
Implementation of the (dynamic) stochastic dual dynamic integer programming (SDDiP) algorithm.
Julia modeling interface to parallel decomposition solver DSP
Input data and source code for the paper "Modelling uncertainty in coupled electricity and gas system models—is it worth the effort?"
Implement integer-L-shaped method for solving two-stage stochastic programming
Solution of a two-stage stochastic model useful for investment planning using pyomo and mpi-sppy.
Devising an optimal portfolio choosing strategy based on stochastic programming
02435 - Decision-Making under Uncertainty
Codebase for "A learning-based algorithm to quickly compute good primal solutions for Stochastic Integer Programs"
reading SMPS format files in C++ (Two-stage stochastic programs with fixed recourse)
Stochastic linear program for investments in the European power system. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711021001424
Stochastic Optimization and ARIMA Model Forecast in Julia to Manage Airline Fleet
GNU MathProg EDSL for Scala with support for scenario-based multistage stochastic programming
reading SMPS files in Python (A Python package for reading SMPS files using GUROBI optimizer objects)
Optimizing Costs for Cloud Computing with Stochastic Programming
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