🎯 A comprehensive gradient-free optimization framework written in Python
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Updated
Jul 19, 2019 - Python
🎯 A comprehensive gradient-free optimization framework written in Python
[JMLR-2024] PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially their *Large-Scale* versions/variants (-> evolutionary algorithms/swarm-based optimizers/pattern search/...).
A next-gen Lagrange-Newton solver for nonconvex optimization. It unifies barrier and SQP methods in a modern and generic way, and implements different globalization flavors (line search/trust region and merit function/filter method/funnel method). Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.
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 simple, bare bones, implementation of simulated annealing optimization algorithm.
Estimation of Distribution algorithms Python package
A Recommender System for Metaheuristic Algorithms for Continuous Optimization Based on Deep Recurrent Neural Networks
Local searches for continuous optimization implemented in C#
C++ lib to perform continuous and combinatorial optimization metaheuristics with parallelism support.
Optimization framework based on swarm intelligence
Predmet: Nelinearno programiranje i evolutivni algoritmi Tema: Genetski algoritam, problem optimizacije kontinualnih funkcija Tri funkcije su: (Ackley, Griewank, Michalewicz )
Code for Dividing Rectangles Attack Multi-Objective Optimization
Javascript implementations of some of the main metaheuristic algorithms for bound constraint single objective continuous optimization problems.
Project in the field of optimisation, in the context of a course from a master of mathematics, at Sorbonne University.
Memetic algorithms for continuous optimization
Yriser is an Open Source FinOps tool to perform AWS tagging best practices, tagging strategy, continuous adjustments in cloud optimization.
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.
Numerical optimisation methods including the cauchy point, dogleg point, line search and steepest descent.
Adaptive Multi-Population Optimization Algorithm
An R Package for Fitting Functional Models to 2-Dimensional Data
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