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)

pyHarmonySearch is a pure Python implementation of the harmony search (HS) global optimization algorithm.

Meta-heuristic optimisation suite for python

Algorithms for flight scheduling optimization.

How to solve the traveling salesman problem with the 2-opt algorithm, a fast heuristic search algorithm.

My n-puzzle solver: A* and IDA* search, heuristics, different puzzle configurations and sizes

⚡ A simulation of finding the shortest charging routes for electric vehicle fleets using ant colony optimization.

This repository implements various Search Based (Heuristic and Incremental) and Sampling Based (Multi Query and Single Query) motion planning algorithms using ROS and turtlebot

AI classic search algorithms with graph and program implementation

Using heuristic search Best-First and A* with BFS (with manhatan distance) methods to solve 8-puzzle

Heuristics for cardinality constrained portfolio optimisation

As alternative heuristic techniques; genetic algorithm, simulated annealing algorithm and city swap algorithm are implemented in Python for Travelling Salesman Problem. Details on implementation and test results can be found in this repository.

This is the A Star algorithm Python implementation

A code to solve 8 Puzzle game using A star algorithm.

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

8 Puzzle solver using uninformed and informed search algorithms as DFS, BFS and A*.

As alternative heuristic technique; tabu search algorithm is implemented in Python for a capacitated plant location (CPL) problem. Details on implementation and test results can be found in this Github repository.

Adapted GRASP algorithm developed by researchers from the Informatics Center of the Federal University of Pernambuco - UFPE to optimize Deep Learning architectures for tabular data classification.

A Travelling Salesman Problem (TSP) solver using a hybrid of strategies