A project on improving Neural Networks performance by using Genetic Algorithms.

A-List of all the Assignment done in Artificial Intelligence Course @IIIT-D

Implementation of metaheuristic optimization methods in Python for scientific, industrial, and educational scenarios. Experiments can be executed in parallel or in a distributed fashion. Experimental results can be evaluated in various ways, including diagrams, tables, and export to Excel.

Convolutional Genetic Programming method for image classification

Implementation of Genetic Algorithm, Memetic Algorithm and Constraint Satisfaction on a Time Table scheduling problem. Also has an implementation of MiniMax Strategy for TicTacToe

A Bionomic Algorithm for the Aircraft Landing Problem

Implementation about a memetic algorithm, including a genetic algorithm and local search for our defined Minesweeper game.

A genetic algorithm to solve the traveling salesman problem

This work was aimed at finding methods to identify the most distant proteins and most diverse subsets of proteins from large protein databases in a scalable and efficient way using a dataset of protein embeddings from SwissProt, data mining techniques and metaheuristics.

The implementation of the paper Solving the Latin Square Completion Problem by Memetic Graph Coloring

Symmetric Cipher Breaking Using Genetic and Memetic Algorithms