Memetic algorithms for continuous optimization
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Updated
May 2, 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.
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
Yriser is an Open Source FinOps tool to perform AWS tagging best practices, tagging strategy, continuous adjustments in cloud optimization.
(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++ platform to perform continuous and combinatorial optimization metaheuristics with parallelism support for acceleration.
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. https://pypop.rtfd.io/
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