Different meta-heuristic optimization techniques for feature selection
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Updated
May 19, 2020 - Python
Different meta-heuristic optimization techniques for feature selection
A list of optimization algorithms and their sample codes
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…
Search for a model and corresponding hyperparameters that best model your data
A collection of the most commonly used Optimisation Algorithms for Data Science & Machine Learning
A Python implementation of the paper "Duelist Algorithm: An Algorithm Inspired by How Duelist Improve Their Capabilities in a Duel" https://arxiv.org/abs/1512.00708
The codes for metaheuristic optimization algorithms
This is a project of portfolio optimization using Quantum-inspired Tabu Search and Trend Ratio
Demonstration of Particle Swarm Optimization (Auto Hyperparameter variant).
A toolkit for MetaHeuristics implemented in Python
Genetic Algorithm as an approach to select image restoration parameters that provides the greatest improvement to a turbid underwater image.
Tabu Search algorithm for the Crew Scheduling Problem, using a modified Prins encoding.
Algorithmes de selection de variables pour préparer un apprentissage non supervisé. La version finale du programme est sélectionne les prédicteurs les plus pertinents en effectuant un apprentissage à chaque génération. La métrique optimisée (dans le cadre du dataset utilisé) est l'accuracy. Nous avons testé les deux métaheuristiques sur un datas…
A Python package to solve Countdown's number round using metaheuristics.
A unpublished package of variant of Quantum-inspired Tabu Search
This research proposes a novel order batching approach for warehouses to minimize total tardiness, considering category, weight, and fragility constraints. A Set-based Mayfly Algorithm (SBMA) is developed, adapting the Mayfly Algorithm to the discrete problem and leveraging swarming/mating behaviors to avoid local optima.
A tool to automatic design Multiple-Stub Matching Networks (MSMN) for wideband on Transmission Lines, using Metaheuristics Optimization Algorithms.
This project implements two nature-inspired optimization algorithms: Moth Flame Optimization (MFO) and Honey Badger Optimization (HBO). Both algorithms are designed to solve complex optimization problems by mimicking behaviors observed in nature. also it includes a path finding algorithm, A-star
An OCaml implementation of the paper https://www.researchgate.net/project/Improved-Harris-Hawk-Optimization
A set of heuristics for finding a minimum weight triangulation of a point set.
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