# tsp-rs [![CircleCI](https://circleci.com/gh/stoksc/tsp-rs.svg?style=svg)](https://circleci.com/gh/stoksc/tsp-rs) Library for traveling salesman problem algorithms. ## Example ### Basic For 2d point datasets: ```rust use std::time; use tsp_rs::Tour; use tsp_rs::point::Point; let tour: Vec<Point> = vec![ Point::new(0., 0.), Point::new(0., 1.), Point::new(1., 0.), Point::new(1., 1.), ]; let mut tour = Tour::from(&tour); tour.optimize_kopt(std::time::Duration::from_secs(1)); ``` ### Using traits Same as above, but instead of using `tsp::point::Point`, just implement the trait `tsp::metrizable::Metrizable` for your type `T` by defining a distance function between two `T`. Your type will also need `Clone`, `Borrow`, maybe another.. the compiler will remember. ## Performance `Path::solve_kopt` uses a 2-opt heuristic with 3-opt thrown in if it hits a wall for too long. Gets to within ~8% of the optimal solution for the b52 and ~10% of qa194 on average in a run of solve_nn + 1 second of optimization. The larger the problem, the longer you should allow for optimization. For the constructive solution, `Path::solve_nn`, gets to within ~15% of the optimal solution on average. ## Comments Just for my own entertainment while learning rust, don't trust this but the implementation should be correct.