Projeto e implementação de um sistema para resolução do problema de alocação de horários utilizando a meta-heurística Simulated Annealing. Trabalho realizado no 5º período de Ciência da Computação do Instituto Federal de Minas Gerais(IFMG) - Campus Formiga para a Disciplina Inteligência Artificial.

Project for CS 170 - Algorithms at UC Berkeley

A Python package to solve Countdown's number round using metaheuristics.

Extreme Learning Machine and Meta-heuristic algorithms implemented in C using threads to solve a Feature Selection problem related to the generation of Seawave Energy

This app calculate the optimized route between multiple locations added by user on google maps. stating position and ending position remains same. It gives you a optimized sequence of places to travel so that all places could be covered in minimum distance exactly once. This project is sub part of my another project Carbon Footprint Calculator.

Courseworks of VLSI Physical Design Automation, NTHU CS course teached by prof. Ting-Chi Wang in fall 2023

Implementation of Hill Climber and Simulated Annealing algorithms

Text Set Cover Problem - Statistical and Deterministic approaches in comparison with simmulated-annealing and greedy algorithms.

Simulated Annealing for optimization mathematical equation

Different algorithms to solve the TSP

Put people in the right places at working using 3 optimization algorithms (Ant Colony Optimization, Simmulated Annealing and Genetic Algorithm built from the ground up with Racket)

Solving TSP with metaheuristic and exact algorithms.

Optimization software for QI Lab. Interfaces with hardware and uses Simulated Annealing Optimization to maximize photon count.

✈️💼 Travelling Salesman Problem approached using the Simmulated Annealing algorithm

Projects and assignments for the Artificial Intelligence course at UCM, with topics such as: Problem representation , solving and search. Heuristic search algorithms. Genetic algorithms. Recommender systems. Machine learning.

Simulación del cálculo de una ruta a de descenso por un cráter en marte con algoritmos de búsqueda local.

This repository seeks to optimize bikes distribution of a public bicycle renting service across city stations using local search algorithms like Hill Climbing and Simulated Annealing, aiming to minimize costs and efficiently meet demand. It includes tools to visualize the distribution and showcases the utility of AI in urban logistics.

N-Queen(s) Problem implemented using Simulated Annealing Algorithm in Python Language