Nerozud's repositories
FTS_simpel
This repository contains Python scripts that demonstrate how to use Plant Simulation as a learning environment for Reinforcement Learning (RL) algorithms to tackle deadlock situations in Automated Guided Vehicle (AGV) systems. The code is compatible with the Gymnasium and Ray libraries.
NEAT_THFS
Application of NeuroEvolution of Augmenting Topologies (THFS) for solving a Two-Stage Hybrid Flow Shop (THFS) scheduling problem with family-sequence dependent setup times. We use the python-neat implementation Alan McIntyre, Matt Kallada, Cesar G. Miguel and Carolina Feher da Silva (https://github.com/CodeReclaimers/neat-python) in conjunction with a discrete event simulation (DES) model of the THFS problem. The DES model was built with the library salabim developed by Ruud van der Ham (https://github.com/salabim/salabim).