Python bindings for OptFrame C++ Functional Core

OptFrame - Optimization Framework

AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.

Reinforcement learning driven TabuCol, for solving the graph coloring problem

Tabu Search implementation for the Knapsack problem.

This is my implementation of a branch and price algorithm to solve the humanitarian aid distribution problem. This problem is a VRP with a specific objective function

Python program for aggregation and reaction

HS Research Project combining Tabu search and Genetic Algorithm for Timetable Scheduling

TSP optimization, Operations Research 2 project, UniPD 2022/23

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

GRASP, Tabu Search and SA for TOPTW

Python3 code for gradient-free global optimization

A Metaheuristic Solver for Multi-Agent Pathfinding Problem

Project for the "Advanced Data Structures and Algorithms" Curricular Unit (FEUP) - VRP Solver

Algorithms for creating short forms based on psychometric principles.

This repository contains various approaches to solving the Traveling Salesman Problem implemented in C++.

C++ metaheuristics modeler/solver for general integer optimization problems.

This repository contains all the assignments that I completed for AI. It includes ILS, Tabu Search, Genetic Algorithms, Genetic Programming, Ant Colony Optimization and Decision Trees

Optimization model made with python, to try to get the best solution for a ficcional problem proposed.

My Masters Thesis

A header-only C/C++ library for solving QUBO problems through Tabu Search.

Solving TSP using Tabu search

A toolkit for MetaHeuristics implemented in Python

NTU Manufacturing Data Science (111-1 )

Traveling Salesman Problem solved with metaheuristics: Tabu Search and Ant Colony System.

My MAX-SAT solver uses stochastic local search, tabu search, and simulated annealing.

Routing problem in heterogeneous fleet is discussed.

Solving Sudoku boards using stochastic methods and genetic algorithms