🎯 A comprehensive gradient-free optimization framework 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 (including evolutionary algorithms, swarm-based randomized optimizers, pattern search, and random search). [https://jmlr.org/papers/v25/23-0386.html] (Its Planned Extensions: PyCoPop7, PyNoPop7, PyDPop77, and PyMePop7)

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 framework 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

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

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

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

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

Optimization framework based on swarm intelligence

Local searches for continuous optimization implemented in C#

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

(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.

Memetic algorithms for continuous optimization