7 papers
MathOptAI.jl: Embed trained machine learning predictors into JuMP models
Oscar Dowson, Robert B Parker, Russel Bent
We present \texttt{MathOptAI.jl}, an open-source Julia library for embedding trained machine learning predictors into a JuMP model. \texttt{MathOptAI.jl} can embed a wide variety o…
Tightening optimality gap with confidence through conformal prediction
Miao Li, Michael Klamkin, Russell Bent +1
Decision makers routinely use constrained optimization technology to plan and operate complex systems like global supply chains or power grids. In this context, practitioners must…
Variable aggregation for nonlinear optimization problems
Sakshi Naik, Lorenz Biegler, Russell Bent +1
Variable aggregation has been largely studied as an important pre-solve algorithm for optimization of linear and mixed-integer programs. Although some nonlinear solvers and algebra…
Nonlinear Optimization with GPU-Accelerated Neural Network Constraints
Robert Parker, Oscar Dowson, Nicole LoGiudice +2
We propose a reduced-space formulation for optimizing over trained neural networks where the network's outputs and derivatives are evaluated on a GPU. To do this, we treat the neur…
A General and Streamlined Differentiable Optimization Framework
Andrew W. Rosemberg, Joaquim Dias Garcia, François Pacaud +5
Differentiating through constrained optimization problems is increasingly central to learning, control, and large-scale decision-making systems, yet practical integration remains c…
Transient Stability-Constrained OPF: Neural Network Surrogate Models and Pricing Stability
Manuel Garcia, Nicole LoGiudice, Robert Parker +1
A Transient Stability-Constrained Optimal Power Flow (TSC-OPF) problem is proposed that enforces frequency stability constraints using Neural Network (NN) surrogate models. NNs are…