Efficiently collect data from geographically distributed locations

This project demonstrates route optimization algorithms (Ant Colony Optimization and Nearest Neighbor) for urban logistics using real geographical coordinates and travel time data from the OpenRouteService API. It supports animated map visualizations and performance analysis.

High-performance weighted Voronoi stippling implementation. Exports PNG and TSP files. Visualizes TSP tours as continuous line drawings.

A Streamlit app that finds the most time-efficient route between multiple addresses using the Google Maps API. Supports various transportation modes and generates a shareable Google Maps link with the optimized route.

Python REST client and examples for DNA-Evolutions TourOptimizer

TravelingSalesman: An alternative algorithm for the Traveling Salesman Problem using convex hull midpoints. This modified greedy approach offers a unique method for path optimization.

Desktop application that obtain the best route possible visiting all nodes with the least time possible using coordinates extracted from a text file.

Solving the Traveling Salesman Problem using Self-Organizing Maps

Solve the TSP problem under simplified assumptions

Traveling Salesman Problem

A python module that calculates delivery routes and displays them in Google Maps.

This is my attempt to solve the Traveling Salesman Problem with a polynomial time algorithm.

Solving the Traveling Sales Person problem using genetic algorithms.

As alternative heuristic techniques; genetic algorithm, simulated annealing algorithm and city swap algorithm are implemented in Python for Travelling Salesman Problem. Details on implementation and test results can be found in this repository.

travelling salesman problem using ortools

Comparison of common algorithms for solving Traveling Salesman Problem.

Route Engine

Recursive kmeans clustering as a traveling salesperson heuristic