Reinforcement learning approach for job shop scheduling
Next-generation scheduling problem solver based on GNNs and Reinforcement Learning
A repository with a data set including instances and results from literature for the Job Shop Scheduling Problem (JSSP). While the raw data is provided as text files, it is also compiled in an R package with an API around it.
python-lekin: Flexible Supply Chain Planning and Scheduler
A Gymnasium Environment for the Job Shop Problem Using the Disjunctive Graph Approach.
The C++ implementation of tabu search for job shop scheduling(JSP). Using N7 neighborhood moves.
This repository provides an OpenAI Gym-compatible environment for production scheduling tasks, designed to benchmark reinforcement learning agents in job shop and flow shop settings.
⚙️ Effortless and efficient task scheduling tailored for production, built with numpy.
Apply DQN to OR-Library ft-06 problem, which gets makespan 58.
Genetic algorithm with a giffler thompson algorithm for JSSP
Repository for pratical work for Natural Computation discipline.
Job Shop Scheduling Problem benchmark instances from http://jobshop.jjvh.nl/ and some utility functions to work with JSP instances.
Ths project provides visualisation for the Job Shop Scheduling Problem. This is focused on Gantt charts. The input date for the visualisation is inspired by plotly's Gantt chart api
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