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)

Capacitated Vehicle Routing Problem solved with Ant Colony Optimization

Simple Python script to extract and generate Adobe Color Swatch (.aco) files

An implementation of the Ant Colony optimization algorithm (ACO) for the capacitated vehicle routing problem (CVRP) for bike sharing rebalancing

Python Implementation of Traveling Salesman Problem (TSP) Using Genetic Algorithms/Hybridized with more Heuristic Optimizations

Used to perform Ant Colony optimisation with Linear Discriminant Analysis for feature reduction in a dataset.

A sophisticated simulation of the Ant Colony Optimization algorithm that employs artificial ants to dynamically navigate a graph, demonstrating emergent pathfinding behaviors through pheromone-based decision-making and iterative exploration strategies.

Bandit and Evolutionary Algorithms using Python

The cMIBACO implementation for lightly robust solutions in MOGenConVRP under uncertainty.

Employing Ant Colony Optimization algorithm to solve maximum clique problem

VRP (Vehicle Routing Problem) solution implemented using Ant Colony Optimization algorithm in Python.

UAV Power Consumtion for Survivability in WPT WSN application

This project is about to find the component failure before it happens in the future. Therefore, a new approach is applied optimization algorithm called Ant colony optimization. This is a preliminary step for this project and still improving on it.

An implementation of the Ant Colony optimisation algorithm for solving Travelling Salesman Problem (TSP)

This web application solves the Traveling Salesman Problem (TSP) using three optimization algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO).ty. The repository provides implementations of three optimization al

Implementation of the Ant Colony Optimization (ACO) algorithm for solving both the classical Travelling Salesman Problem (TSP) and a variant thereof with additional non-mandatory nodes. Additionally, implementing a few variants of ACO and comparing the results.

Repository for pratical work for Natural Computation discipline.

Swarmpy_tsp is a Python Library to easily build customizable Ant Colony Optimization pipelines for solving Traveling Salesman Problems

Overview This project demonstrates the use of Ant Colony Optimization (ACO) to analyze and optimize reservoir datasets provided by CDAC Pune. The project integrates data preprocessing, feature engineering, and constraint handling to model the behavior of reservoirs and improve decision-making processes.

Convert ASE palettes to ACO palettes