[JMLR (CCF-A)] PyPop7: A Pure-PYthon LibrarY for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* algorithm variants. In the near future, we will add Learning-Based Optimizers as its extensions. [https://jmlr.org/papers/v25/23-0386.html]

Solver for Large-Scale Rank-One Semidefinite Relaxations

Code and computational experiments of the paper "Benders Adaptive-Cuts Method for Two-Stage Stochastic Programs" by Cristian Ramírez-Pico, Ivana Ljubić and Eduardo Moreno. arXiv:2203.00752

The SAG (Stochastic Average Gradient) + SAGA (Accelerated) solver is an optimization algorithm used primarily in machine learning, specifically for logistic regression and linear support vector machines (SVMs) within libraries like scikit-learn. It is designed to be highly efficient for large datasets with many samples and features. Solver

Rapid Optimization Library

A ray-based library of Distributed POPulation-based OPtimization for Large-Scale Black-Box Optimization.

LSQR is an iterative method for solving large, sparse, linear systems of equations and linear least-squares problems, including under- or over-determined and rank-deficient systems. It uses the Lanczos bidiagonalization process to provide a robust alternative to conjugate gradients, offering better numerical stability. Solver

Linear regression with the LBFGSB (Limited-memory Broyden-Fletcher-Goldfarb-Shanno BFGS) solver method is a numerical optimization method used to find the minimum of an objective function. It is a gradient descent algorithm that uses an approximation of the Hessian matrix to minimize the function.

The Conjugate Gradient (CG) method is an efficient iterative algorithm for solving large, sparse systems of linear equations where the matrix is symmetric and positive-definite. It finds the minimum of a quadratic function by generating conjugate search directions, ensuring convergence in at most steps for an matrix.Solver

Compressed Radiation Treatment Planning [NeurIPS'24, MP'2025, PMB'23]

A GPU-Accelerated First Order Solver for Convex Quadratic Programming

A First-Order LP Solver Accelerated on Multiple GPUs

Build content-based image retrieval system using deep learning, applied some large scale similarity search technicals like Kdtree, LSH, Faiss.

Network-wide estimation of traffic flow and travel time with data-driven macroscopic models

Distributed Low-Memory Matrix Adaptation (D-LM-MA) Evolution Strategy.

Operations research projects will be added in this repo

A pure-MATLAB library of EVolutionary (population-based) OPTimization for Large-Scale black-box continuous Optimization (evopt-lso).

A deep reinforcement learning system for optimizing bridge maintenance decisions across municipal infrastructure fleets, implementing cross-subsidy budget sharing and cooperative multi-agent learning.

A pure-MATLAB library for POPulation-based Large-Scale Black-Box Optimization (pop-lsbbo).

This repository provides practical implementations, examples, and insights into various optimization methods, making it easier to understand and apply these concepts.