A comprehensive Python implementation comparing multiple metaheuristic algorithms for solving the Vehicle Routing Problem with Time Windows (VRPTW). It provides a detailed comparison of four state-of-the-art optimization algorithms: Hybrid Genetic Search (HGS), Guided Local Search (GLS), Ant Colony Optimization (ACO), Simulated Annealing (SA)

Python wrapper of Sparrow, State-of-the-art Nesting for 2D irregular strip packing

An interactive map of local businesses in Leipzig.

EVRPTW resolution with Ant Colony Optimization

A computational intelligence project exploring metaheuristic algorithms for combinatorial optimization, developed for the Artificial Intelligence course at FEUP.

code to scrape google maps results for tracking local seo rank

EvoRBF: A Nature-inspired Algorithmic Framework for Evolving Radial Basis Function Networks

Python bindings for OptFrame C++ Functional Core

Code accompanying the paper "Small Ramsey numbers for books, wheels, and generalizations"

Solving VRPTW with metaheuristics

OpenDeepSearch tool configured for Ollama, SearXNG, Reranking, Custom prompt - fully local and free.

Optimizing the bin packing problem, aiming to efficiently allocate items of varying sizes into a finite number of bins while maximizing total profit, using optimization algorithms

Python implementation of the Knowledge Guided Local Search (KGLS) for Vehicle Routing Problems (VRP)

This assignment was done as part of COL333 Course Requirements. This project involved the development of an Automatic Speech Recognition (ASR) corrector utilizing a local beam search strategy to improve the text outputs from ASR systems.

Course assignments of COL333:- Artificial Intelligence course at IIT Delhi under Professor Rohan Paul

Sudoku Solver is a repository dedicated to the development and benchmark of famous and novel approaches to solve Sudoku puzzles up to 17 clues

A coding project aimed at exploring new ways of algorithmic learning using evolutionary techniques such as genetic algorithms and crossover

Solver for the radio link frequency assignment CSP

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.

Implementation and comparison of a number of different approaches for solving a resource assignment scheduling problem.