Project in the field of optimisation, in the context of a course from a master of mathematics, at Sorbonne University.
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Updated
Jan 5, 2020 - MATLAB
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++ 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 nonlinearly constrained nonconvex optimization. Reimplements filterSQP (trust-region filter SQP) and IPOPT (line-search filter barrier) in a modern and abstracted way. Unlocks methods never seen before. 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/
🎯 A comprehensive gradient-free optimization framework written in Python
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