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.

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

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.

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

A High-Performance C++ Toolkit for solving classic TSP instances with B&B.

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

Comparative metaheuristics for the Sequential Ordering Problem (SOP): Genetic Algorithm vs Particle Swarm Optimization on TSPLIB-SOP.

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.

A full-stack algorithm visualization platform developed as a university team project to compare multiple approaches to the Traveling Salesman Problem, including exact, heuristic, approximation, and LLM-generated solutions.

Few implementations of algorithms solving Travelling Salesman Problem