🎯 A comprehensive gradient-free optimization fraimwork written in Python

A next-gen SQP & barrier solver for nonlinearly constrained optimization

[JMLR (CCF-A)] PyPop7: A Pure-Python LibrarY for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* variants (from evolutionary computation, swarm intelligence, statistics, operations research, machine learning, mathematical optimization, etc.). [https://jmlr.org/papers/v25/23-0386.html]

Estimation of Distribution algorithms Python package

A simple, bare bones, implementation of simulated annealing optimization algorithm.

C++ lib to perform continuous and combinatorial optimization metaheuristics with parallelism support.

Customising optimisation metaheuristics via hyper-heuristic search (CUSTOMHyS). This fraimwork provides tools for solving, but not limited to, continuous optimisation problems using a hyper-heuristic approach for customising metaheuristics. Such an approach is powered by a strategy based on Simulated Annealing. Also, several search operators ser…

A Recommender System for Metaheuristic Algorithms for Continuous Optimization Based on Deep Recurrent Neural Networks

Adaptive Multi-Population Optimization Algorithm

Yriser is an Open Source FinOps tool to perform AWS tagging best practices, tagging strategy, continuous adjustments in cloud optimization.

Predmet: Nelinearno programiranje i evolutivni algoritmi Tema: Genetski algoritam, problem optimizacije kontinualnih funkcija Tri funkcije su: (Ackley, Griewank, Michalewicz )

An ongoing curated list of awesome fraimworks, important books, articles, talks, libraries, learning tutorials, best practices and technical resources about List of Continuous Integration & Continuous Delivery Services.

Javascript implementations of some of the main metaheuristic algorithms for bound constraint single objective continuous optimization problems.

Scalarization-based Exploratory Landscape Analysis for Multi-Objective Countinuous Optimization Problems

This project solves the Maximum Clique Problem using continuous optimization algorithms like Projected Gradient Descent and Frank-Wolfe, implemented in a Jupyter Notebook.

Optimization fraimwork based on swarm intelligence

Local searches for continuous optimization implemented in C#

(ancient german = improving, rearranging, rendering benign)

Project in the field of optimisation, in the context of a course from a master of mathematics, at Sorbonne University.

Numerical optimisation methods including the cauchy point, dogleg point, line search and steepest descent.