Welcome to MSP’s documentation!¶
Welcome to the Machine Scheduling Problem (MSP) python package guide!
MSP python package offers a deep reinforcement learning model based on low-level API of tensorflow. It addresses the MSP problem especially for the Fabric Industry. However, the presented method is not only limited to it.
NOTE: This package has been built during the research internship at LIMOS in Clermont-Ferrand, France
In this research, we design Deep Learning model to sovle MSP problem (NP-hard combinatorial optimization problem) where the goal is to find a schedule from combinatorial search space such that it minimizes makespan (i.e., an objective) under certain constraints.
To define the MSP problem, we employ graph structure to model the various interaction between machines and jobs. We cast the MSP as a Graph-to-Sequence machine learning problem that follows the standard encoder-decoder architecture consisting of graph encoder, and a recurrent decoder. We train the model using a policy-gradient reinforcement learning algorithm, namely REINFORCE algorithm. Furthermore, we also present different novel masking strategies to filter out the invalid action at any timestep during the decoding.
To access the full research document, send the Request Email to mohammedbilalansari.official@gmail.com
If you want to use this package follow the instructions to install it.