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)

A Vehicle Routing Problem solver

OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.

A python library with implementations of 15 classical heuristics for the capacitated vehicle routing problem.

A collection of NVIDIA cuOpt samples and other resources

[NeurIPS 2023] DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

Improve Warehouse Productivity using Order Batching

A Python wrapper for the Hybrid Genetic Search algorithm for Capacitated Vehicle Routing Problems (HGS-CVRP)

Library for working with TSPLIB files.

A Kotlin implementation of the TSP problem, with TornadoFX Visualization

ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution

Julia package for simple traveling salesman problem heuristics

A dependency free library of standardized optimization test functions written in pure Python.

Genetic algorithm for Traveling salesman problem

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

A simple, bare bones, implementation of simulated annealing optimization algorithm.

Simple Traveling Salesman Problem implementation in Julia

Genetic Algorithm + Google Maps API to solve the Traveling Salesman (NP-hard) Problem. Plan your travel over 100+ places with ease.

A Greedy Randomized Adaptive Search Procedure (GRASP) for the Traveling Salesman Problem (TSP)

metaheuristics for traveling salesman problem (TSP)