HiGHS - High-performance parallel linear optimization software HiGHS is high performance serial and parallel software for solving large-scale sparse linear programming (LP), mixed-integer programming (MIP) and quadratic programming (QP) models, developed in C++11, with interfaces to C, C#, FORTRAN, Julia and Python
GitHub - ERGO-Code HiGHS: Linear optimization software HiGHS has primal and dual revised simplex solvers, originally written by Qi Huangfu and further developed by Julian Hall It also has an interior point solver for LP written by Lukas Schork, an active set solver for QP written by Michael Feldmeier, and a MIP solver written by Leona Gottwald
HiGHS optimization solver - Wikipedia HiGHS is designed to solve large-scale models and exploits problem sparsity Its performance relative to commercial and other open-source software is reviewed periodically using industry-standard benchmarks
About · HiGHS Documentation - GitHub Pages HiGHS is software for the definition, modification and solution of large scale sparse linear optimization models HiGHS is freely available from GitHub under the MIT licence and has no third-party dependencies
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HiGHS - GAMS HiGHS is an optimization package for solving continuous and mixed-integer linear programming problems (LPs and MIPs) using simplex, interior-point, primal-dual hybrid gradient, and branch-and-cut algorithms