Leopard is a fast, modern implementation of sparse, multifrontal symmetric indefinite matrix factorization.
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Updated
Oct 5, 2023 - C++
Leopard is a fast, modern implementation of sparse, multifrontal symmetric indefinite matrix factorization.
simulation of actual demand of electricity load.
This jupyter notebook uses the pyomo optimization library and ipopt solver to fit water advancement data based on the Y = X ^ r equation. This equation is used to model the advancement of water in border irrigation. X represents advancement time (min) and Y represents advancement length (m) '''
Access to the Ipopt C Interface from Rust via bindgen
Model Predictive Control vehicle controller project of the Udacity Self-Driving Car Engineer Nanodegree
This repo collects results of nonlinear optimization solvers on standard benchmark problems
Optimal MPMVC-based truss structures using the Augmented Lagrangian Method
Discovering faster matrix multiplication algorithm with optimization
This is an implementation of an interior-point algorithm with a line-search method for nonlinear optimization. This package contains several subdirectories corresponding to COIN-OR projects. The AUTHORS, LICENSE and README files in each of the subdirectories give more information about these projects.
Sketches of model-based control ideas for gym classic control
Assignment to learn Nonlinear Constrained Optimization with Ipopt
Solution to the p-Median and Maximal Coverage Location problems by defining the objective function, set, parameters and constraints visually and mathematically. Solvers: gurobipy, pyomo, ipopt.
A nonlinear model predictive controller for an autonomous vehicle in a simulation environment.
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