tlbo-optimization 0.1.0

Teaching-Learning-Based Optimization (TLBO) algorithm

Teaching-Learning-Based Optimization (TLBO) algorithm

Overview

The TLBO algorithm is a population-based optimization technique inspired by the teaching-learning process. This package provides an easy-to-use implementation of TLBO for optimizing various objective functions.

Features

• Simple and intuitive interface for using TLBO

• Supports multiple objective functions

• Customizable parameters such as population size, number of dimensions, and bounds

• Efficient optimization for various types of problems

Installation

You can install the package using pip:

pip install tlbo-optimization

Example

Here is an example of how to use the TLBO algorithm:

from tlbo_optimization.tlbo_optimization import TLBO

def objective_function(x):
    return sum(x ** 2)

tlbo = TLBO(
    population_size=30,
    dimensions=5,
    lower_bound=-10,
    upper_bound=10,
    max_iter=100,
    obj_func=objective_function
)

best_solution, best_fitness = tlbo.optimize()

print(f"Best solution: {best_solution}")
print(f"Best fitness: {best_fitness}")

Contributing

Contributions are welcome! Please read the CONTRIBUTING.rst for details on how to contribute.

License

This project is licensed under the GNU General Public License v3.