OptFrame - Optimization Framework

An R package to create and visualise fast-and-frugal decision trees (FFTs)

STEM Fellowship Computing Indicium Team: TSP Code

a set of implementations of TSP heuristics with a focus on readability

Guess the indentation of a JSON string.

This is a repository that compiles archives of past heuristic contests.

This program will approximate the Traveling salesman problem using 3 three different algorithms (Nearest Neighbot, 2Opt, and 3Opt). There are 6 different combinations and each can be run individually or in suite as part of a benchmark test.

Visualization of several well-known graph pathfinding algorithms using Rust programming language with pixels crate for graphics

Notebooks focused on optimization algorithms that are designed to solve the flowshop problem.

Functions, examples and data from the book "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2011), ISBN 978-0123756626.

better google maps for block game

Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). This repository mirrors https://gitlab.com/NMOF/NMOF .

Code for "ELLEN: Extremely Lightly Supervised Learning For Efficient Named Entity Recognition" (LREC-COLING 2024)

Pure Python (3.12.1) implementation of K-means clustering for float values.

Approaching the PFS problem with an Object-Oriented Design

Code for Specifying Goals to Deep Neural Networks with Answer Set Programming

🗺️ Visualize and control algorithms for the traveling salesman problem

Esse projeto tem como objetivo tratar sobre a simulação de conceitos evolucionários com o intuito de validar algumas teorias genéticas. No momento, algumas meta-heuristicas famosas estão implementadas neste repositórios, como: Ant Algorithm, PSO, Clonalg, DE Algorithm, Evolutionary Island Model Algorithm and Genetic Algorithm.

This problem grabbed my attention and I decided to study it further and share some interesting solutions I have developed.

Developed innovative optimization and ML algorithms to tackle data science tasks, including classification and sparse recovery, focusing on the NP-hard Maximum Feasible Subsystem problem.