Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
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Updated
May 9, 2024 - Julia
Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
A Julia/JuMP Package for Maximizing Algebraic Connectivity of Undirected Weighted Graphs
COSMO: Accelerated ADMM-based solver for convex conic optimisation problems (LP, QP, SOCP, SDP, ExpCP, PowCP). Automatic chordal decomposition of sparse semidefinite programs.
Clarabel.jl: Interior-point solver for convex conic optimisation problems in Julia.
Clarabel.rs: Interior-point solver for convex conic optimisation problems in Rust.
Splitting Conic Solver
PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.
Tools to compute the minimum semidefinite rank of a simple undirected graph
Computational appendix of arXiv:2403.02376
An Exact Solver for Cardinality-constrained Minimum Sum-of-Squares Clustering
An Exact Solver for Semi-supervised Minimum Sum-of-Squares Clustering
An Exact Solver for Minimum Sum-of-Squares Clustering
Documentation for the Clarabel interior point conic solver
Irene is a python package that aims to be a toolkit for global optimization problems that can be realized algebraically. It generalizes Lasserre's Relaxation method to handle theoretically any optimization problem with bounded feasibility set. The method is based on solutions of generalized truncated moment problems over commutative real algebras.
Clarabel.cpp: C/C++ interface to the Clarabel Interior-point solver for convex conic optimisation problems.
Code of the Performance Estimation Toolbox (PESTO) whose aim is to ease the access to the PEP methodology for performing worst-case analyses of first-order methods in convex and nonconvex optimization. The numerical worst-case analyses from PEP can be performed just by writting the algorithms just as you would implement them.
A Coq tactic for proving multivariate inequalities using SDP solvers
SemiDefinite Programming Algorithm (SDPA) for Python
An accelerated active‑set algorithm for a quadratic semidefinite program with general constraints
Code for paper "Searching for polarization in signed graphs: a local spectral approach" (published at WebConf 2020)
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