This repository was created for the subject of Computer Theory. The propose of this subject is to improve your skills to solve the 0-1 knapsack problem of different ways. The techniques used were Dynamic Programing and two metaheuristics (which are GRASP and TABU search).

Job Shop Scheduling metaheuristics

GRASP, Tabu Search and SA for TOPTW

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.

Project for Algorithmic Methods for Mathematical Modeling class

Algorithm for solving optimal stocks compression problem in warehouse. The math problem is the Single-Source Capacitated Facility Location Problem.

Master 1 project on operations research 's " Set Covering Problem". Some famous methods (Grasp, simulated annealing) have been used.

This project together with mrcp document explain process of develop and analitic of MRCP or Maximum Ratio Clique Problem. Wich starting from a graph with nodes and different weights of these, the algorithm will find an aproximate optimal solution, forming a clique or a complete sub-graph with maximum ratio.

This repository contains my solutions to the assignments of the course CSE-318 | Artificial Intelligence.

Here is the documentation related to the "mrcp-project" repository for the final degree project in software engineering.

Discrete Optimization

Total energy demand estimation GRASP-ELM algorythm

TSP GRASP

AI course works.Implementation of popular N-puzzle,Mancala and Decision tree

SORTLOT project packing optimizer

Greedy, Greedy+LocalSearch(2-opt), Stocastic and GRASP implementations to solve the Symetric Travelling Salesman Problem (STSP). The TSP instances were taken from the TSPLIB website (http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/)

A solution based on the Maximum Independent Set to solve the Maximum Clique using the GRASP metaheuristic.

Lab codes for Artificial Intelligence Lab of Level 3 Term 2 at BUET CSE undergrad

Implementation of some meta-heuristic algorithms. Include Greedy Randoimnized Adaptive Search Procedure for TSP problem