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A benchmarking repo with various solution methods to various machine scheduling problems

Solve production scheduling problems with constraint programming in Python.

A modular Python library for creating, solving, and visualizing job shop scheduling problems.

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.

An end to end reinforcement learning approach with a reinforcement learning environment modeled as a CP model

Constraint Satisfaction Problem (CSP) Solver

A Python library for implementing and testing algorithm for Job-Shop Scheduling problem.

A Gymnasium Environment for the Job Shop Problem Using the Disjunctive Graph Approach.

Solving the Job-Shop Scheduling Problem (JSSP) with Graph Neural Networks (GNNs).

ScheduleOpt benchmarks

Implementation of job-shop scheduling problem using C#.

⚙️ Effortless and efficient task scheduling tailored for production, built with numpy.

Research code for flow shop, job shop and open shop scheduling problems

Job scheduling with deadlines using quantum annealing

Metaheuristic- and RL-powered production scheduling & optimization toolkit in Python

Job Shop Scheduling Problem benchmark instances from http://jobshop.jjvh.nl/ and some utility functions to work with JSP instances.

A Matlab-based Hyper-Heuristic framework. To cite this Original Software Publication: https://www.sciencedirect.com/science/article/pii/S2352711022000413