Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
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Updated
Nov 14, 2024 - Julia
Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
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.
Toolbox for gradient-based and derivative-free non-convex constrained optimization with continuous and/or discrete variables.
Semidefinite programming optimization solver
A Julia/JuMP Package for Maximizing Algebraic Connectivity of Undirected Weighted Graphs
Documentation for the Clarabel interior point conic solver
A Julia package for the computation of hard, theoretically guaranteed bounds on the moments of jump-diffusion processes with polynomial data
A parallelized, arbitrary precision semidefinite program solver based on the primal-dual interior-point method.
A Julia interface to the SDPA semidefinite programming solver
A Julia interface to the DSDP semidefinite programming solver
A collection of semidefinite programs that can be randomly generated. Taken from various applications.
Codes for the paper: Theoretical bounds on the network community profile from low-rank semi-definite programming
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