PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially their *Large-Scale* versions/variants. https://pypop.rtfd.io/
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Updated
Jun 5, 2024 - Python
PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially their *Large-Scale* versions/variants. https://pypop.rtfd.io/
A next-gen solver for optimization with nonconvex objective and constraints. Reimplements filterSQP and IPOPT (barrier) in a modern and generic way, and unlocks a variety of novel methods. Competitive against filterSQP, IPOPT, SNOPT, MINOS and CONOPT.
Memetic algorithms for continuous optimization
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…
Estimation of Distribution algorithms Python package
(ancient german = improving, rearranging, rendering benign)
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.
A simple, bare bones, implementation of simulated annealing optimization algorithm.
C++ platform to perform continuous and combinatorial optimization metaheuristics with parallelism support for acceleration.
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.
Adaptive Multi-Population Optimization Algorithm
Numerical optimisation methods including the cauchy point, dogleg point, line search and steepest descent.
A Recommender System for Metaheuristic Algorithms for Continuous Optimization Based on Deep Recurrent Neural Networks
Predmet: Nelinearno programiranje i evolutivni algoritmi Tema: Genetski algoritam, problem optimizacije kontinualnih funkcija Tri funkcije su: (Ackley, Griewank, Michalewicz )
Project in the field of optimisation, in the context of a course from a master of mathematics, at Sorbonne University.
🎯 A comprehensive gradient-free optimization framework written in Python
An R Package for Fitting Functional Models to 2-Dimensional Data
Local searches for continuous optimization implemented in C#
Code for Dividing Rectangles Attack Multi-Objective Optimization
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