Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
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Updated
Nov 8, 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.
Represent trained machine learning models as Pyomo optimization formulations
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.
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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