GitHub

IPM-LSTM: A Learning-Based Interior Point Method for Solving Nonlinear Programs

This repository is an implementation of the NeurIPS 2024 paper: IPM-LSTM: A Learning-Based Interior Point Method for Solving Nonlinear Programs. Constrained Nonlinear Programs (NLPs) represent a ...
Scientific Research Publishing

Zhang, Y. (1996) Solving Large-Scale Linear Programs by Interior-Point Methods under the Matlab Environment, Tech. rep., Department of Mathematics and Statistics, University of ...

ABSTRACT: This work presents a new methodology based on Linear Programming (LP) to tune Proportional-Integral-Derivative (PID) control parameters. From a specification of a desired output time domain ...
CU Boulder News & Events

CSCA 5424: Approximation Algorithms and Linear Programming

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...
IEEE

Solving Mixed Integer Linear Programs by Monte Carlo Tree Search

Abstract: Mixed Integer Linear Programs (MILPs) are powerful tools for modeling and solving combinatorial optimization problems. Solving an MILP is NP-hard due to the integrality requirement, and the ...