Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
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Updated
Sep 28, 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
Represent trained machine learning models as Pyomo optimization formulations
A curated list of mathematical optimization courses, lectures, books, notes, libraries, frameworks and software.
A next-gen solver for optimization with nonconvex objective and constraints. Unifies barrier and SQP methods in a modern and generic way, and unlocks a variety of novel methods. Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.
Efficient modeling interface for mathematical optimization in Python
My sandbox for experimenting with solver algorithms.
Tutorials on using JuMP for mathematical optimization in Julia
Derivative-Free Global Optimization Algorithm (C++, Python binding) - Continuous, Discrete, TSP, NLS, MINLP
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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