Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
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Updated
Nov 26, 2024 - Julia
Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
An object-oriented algebraic modeling language in Python for structured optimization problems.
General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python
Python interface for the SCIP Optimization Suite
An Eigen-based, light-weight C Interface to Nonlinear Programming Solvers (Ipopt, Snopt)
oj! Algorithms
A data structure for mathematical optimization problems
A curated list of mathematical optimization courses, lectures, books, notes, libraries, frameworks and software.
A next-gen Lagrange-Newton solver for nonconvex optimization. It unifies barrier and SQP methods in a modern and generic way, and implements different globalization flavors (line search/trust region and merit function/filter method/funnel method). Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.
Represent trained machine learning models as Pyomo optimization formulations
Efficient modeling interface for mathematical optimization in Python
My sandbox for experimenting with solver algorithms.
Derivative-Free Global Optimization Algorithm (C , Python binding) - Continuous, Discrete, TSP, NLS, MINLP
Tutorials on using JuMP for mathematical optimization in Julia
A library of modern Fortran modules for nonlinear optimization
An Extension Library for Unity.Mathematics - Extension Methods, New Syntax, Optimized Functions, and more !
provides a modeling interface for mixed complementarity problems (MCP) and math programs with equilibrium problems (MPEC) via JuMP
Efficiently solving instances of a parameterized family of (possibly mixed-integer) linear/quadratic optimization problems in Julia
Exact solutions for two-dimensional bin packing problems by branch-and-cut
An algebraic modeling and automatic differentiation tool in Julia Language, specialized for SIMD abstraction of nonlinear programs.
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