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…

Metaheuristic Minimization Using Particle Swarm Optimization.

MetaPerceptron: A Standardized Framework For Metaheuristic-Driven Multi-layer Perceptron Optimization

reflame: Revolutionizing Functional Link Neural Network by Metaheuristic Optimization

X-ANFIS: An Extensible and Cross-Learning ANFIS Framework for Machine Learning Tasks

Adaptive Multi-Population Optimization Algorithm

EvoRBF: A Nature-inspired Algorithmic Framework for Evolving Radial Basis Function Networks

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 .

The codes for metaheuristic optimization algorithms

Enhancing the performance of high dimensional automatic data clustering using Particle Swarm Optimization (PSO) algorithm employing Autoencoder in Stock Market data.

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.

This is a project of portfolio optimization using Quantum-inspired Tabu Search and Trend Ratio

A project for Fundamental of Optimization class at HUST, Winter 2022

(ancient german = improving, rearranging, rendering benign)

So sánh hiệu quả của các thuật toán metaheuristic và lớp thuật toán thử sai (ACO, PSO, Greedy, Branch and Bound) trong bài toán Traveling Salesman Problem (TSP).

Demonstration of Particle Swarm Optimization (Auto Hyperparameter variant).

A toolkit for MetaHeuristics implemented in Python

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

A tool to automatic design Multiple-Stub Matching Networks (MSMN) for wideband on Transmission Lines, using Metaheuristics Optimization Algorithms.