Different meta-heuristic optimization techniques for feature selection
-
Updated
May 19, 2020 - Python
Different meta-heuristic optimization techniques for feature selection
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…
The codes for metaheuristic optimization algorithms
Demonstration of Particle Swarm Optimization (Auto Hyperparameter variant).
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…
Metaheuristic Minimization Using Particle Swarm Optimization.
This is a project of portfolio optimization using Quantum-inspired Tabu Search and Trend Ratio
EvoRBF: Evolving Radial Basis Function Network by Intelligent Nature-inspired Algorithms
A project for Fundamental of Optimization class at HUST, Winter 2022
Simple Python Implementation of Differential Search Algorithm (DSA)
Implementation of some metaheuristic algorithms.
The traveling salesman problem (TSP) is a well-known problem in theoretical computer science and operations research. The standard version of the TSP is a hard problem and belongs to the NP-Hard class. In this project, I build an application to implement the TSP by the dynamic approach and the GVNS approach .
MetaPerceptron: Unleashing the Power of Metaheuristic-optimized Multi-Layer Perceptron - A Python Library
This work was aimed at finding methods to identify the most distant proteins and most diverse subsets of proteins from large protein databases in a scalable and efficient way using a dataset of protein embeddings from SwissProt, data mining techniques and metaheuristics.
(ancient german = improving, rearranging, rendering benign)
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.
CS F407 Project
Current repository contains my implementation of Crystal Structure Algorithm.
Game Playing Agent (Artificial Intelligence) - Solving the Norinori Puzzle using the Honey Badger Algorithm and Q-Learning
Add a description, image, and links to the metaheuristic-algorithms topic page so that developers can more easily learn about it.
To associate your repository with the metaheuristic-algorithms topic, visit your repo's landing page and select "manage topics."