tsplib

This repository implements several swarm optimization algorithms and visualizes them. Implemented algorithms: Particle Swarm Optimization (PSO), Firefly Algorithm (FA), Cuckoo Search (CS), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA)

Library for working with TSPLIB files.

This code is to solve traveling salesman problem by using simulated annealing meta heuristic.

Small lib which generate binary data for tsc printer (tspl tspl2)

Vehicle routing problem instances and best-known solutions for benchmarking.

A C++ implementation of the Christofides algorithm for instances in TSPLIB format

Ant Colony Optimization in Julia

High-performance Evolutionary TSP Solver with Gamified Streamlit UI. Features Hybrid GA (Genetic Algorithm) + 3-Opt Local Search, TSPLIB support (EUC_2D/ATT), and real-time visualization.

A high-performance Rust library for solving the Traveling Salesman Problem (TSP) using the novel Dynamic Gravity algorithm.

Implementation of Ant Colony Optimization (ACO) in Erlang language. Project realized for Computational Intelligence class.

A parser to read TSPLIB format files and convert to full matrix structure.

python module to parse TSPLIB files and obtain distance matrix

🧬 C++ TSP solver using Genetic Algorithm | OX/PMX/Cycle crossover | Swap/Inversion/Scramble mutation | 📊 matplotlib plots | 🗺️ TSPLIB support

A multi-algorithm solver for Travelling Salesman Problem (TSP) focused on automating testing and comparing performance of various algorithms.

An implementation of the Growth Optimizer (GO) algorithm to solve symmetric TSP instances.

Distributed C/MPI parallel-tempering TSP solver with TSPLIB validation and a repeated 1–24 process strong-scaling benchmark.

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

Algorithms of integer linear programming applied to TSP and written report about them.

Exact and metaheuristic TSP solvers in Python — Held-Karp, branch and bound, simulated annealing and ant colony optimization — benchmarked against published TSPLIB optima.

Genetic Algorithm solver for the Traveling Salesman Problem (TSP) with configurable operators — tournament selection, order crossover, swap/inverse mutation. Includes greedy baseline and TSPLIB benchmark datasets.