Just some notebooks I wrote to research some fun stuff in hobby time
-
Updated
Jul 25, 2024 - Jupyter Notebook
8000
Just some notebooks I wrote to research some fun stuff in hobby time
Notebook for demonstrating simulated annealing
Notebook implementing some sudoku solvers.
Analysis of Simulated Annealing algorithm performance using Python and Jupyter Notebook.
Computational Intelligence algorithm resources. Programming Language: Python 3.7 | IDE: Jupyter Notebook
Jupyter notebook to solve the Traveling Salesman Problem (TSP) between US state capitals
Notebooks created for a college assignment where simulated annealing was used to solve the travelling salesman problem.
Jupyter notebooks, scripts, and results associated with the paper Visualization of Optimization Algorithms by Marco Morais (Morais, 2020).
This repository contains Python implementations of the Simulated Annealing optimization algorithm. It includes two Colab notebooks — one that evaluates Simulated Annealing across 55 benchmark functions and another that focuses on a single test function (Ackley) — along with sample result files and documentation.
The travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?" In this notebook, I demonstate the solution of this problem with the simulated annealing algorithm.
Add a description, image, and links to the simulated-annealing topic page so that developers can more easily learn about it.
To associate your repository with the simulated-annealing topic, visit your repo's landing page and select "manage topics."