Google's Operations Research tools:
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Updated
Nov 14, 2024 - C++
Google's Operations Research tools:
Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
An object-oriented algebraic modeling language in Python for structured optimization problems.
Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.
A cryptocurrency arbitrage framework implemented with ccxt and cplex. It can be used to monitor multiple exchanges, find a multi-lateral arbitrage path which maximizes rate of return, calculate the optimal trading amount for each pair in the path given flexible constraints, and execute trades with multi-threading implemenation.
Splitting Conic Solver
Python-MIP: collection of Python tools for the modeling and solution of Mixed-Integer Linear programs
An incremental linear constraint-solving algorithm (Auto Layout) in Swift.
Curso de Álgebra Lineal
Simple OOP javaScript library to solve linear programs, and mixed integer linear programs
The Advanced Proximal Optimization Toolbox
Clarabel.rs: Interior-point solver for convex conic optimisation problems in Rust.
A Rust implementation of the Cassowary constraint solving algorithm
《线性代数及其应用》笔记
emhass: Energy Management for Home Assistant, is a Python module designed to optimize your home energy interfacing with Home Assistant.
A curated list of mathematical optimization courses, lectures, books, notes, libraries, frameworks and software.
Pyomo respository provides a comprehensive library of solved models in Supply chain management
R package to model Mixed Integer Linear Programs
Linear Programming for Rust, with a user-friendly API. This crate allows modeling LP problems, and lets you solve them with various solvers.
General optimization (LP, MIP, QP, continuous and discrete optimization etc.) using Python
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