Memetic algorithms for continuous optimization
-
Updated
Jul 3, 2024 - Java
Memetic algorithms for continuous optimization
Project in the field of optimisation, in the context of a course from a master of mathematics, at Sorbonne University.
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
(ancient german = improving, rearranging, rendering benign)
An R Package for Fitting Functional Models to 2-Dimensional Data
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.
Optimization framework based on swarm intelligence
C++ lib to perform continuous and combinatorial optimization metaheuristics with parallelism support.
Local searches for continuous optimization implemented in C#
A Recommender System for Metaheuristic Algorithms for Continuous Optimization Based on Deep Recurrent Neural Networks
Estimation of Distribution algorithms Python package
A simple, bare bones, implementation of simulated annealing optimization algorithm.
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 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.
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/...). [https://pypop.rtfd.io/]
Add a description, image, and links to the continuous-optimization topic page so that developers can more easily learn about it.
To associate your repository with the continuous-optimization topic, visit your repo's landing page and select "manage topics."