Open shop scheduling in a manufacturing company using machine learning

Abstract—We present a framework based on machine learning for reducing the problem size of a short-term hydrothermal scheduling optimization model applied for price forecasting..

We have provided a concise formal definition of a Complex Job-Shop scheduling problem which generalizes several scheduling problems defined in the literature: It reduces to

During the summer of 2019, a team of students and scientists at the Norwegian Defence Research Establishment (FFI) participated in the Kaggle competition Predicting Molecular

The goal with this thesis is to explore machine learning and the possibilities of using machine learning to create a model that can predict the effect of

Machine Learning Zoo // Links // Data Science, Optimization // Big Data Landscape... From Experiment

The algorithm is implemented with a policy network (the action to take for a given state), a value network (describing how advantageous each state is), a target value network, and

Three machine learning algorithms (the deep neural network (DNN), random forest (RF), and support vector machine (SVM) algorithms) optimized by three hyperparameter search methods

In this research, we will analyze the relationship between weather and the number of citizens using public transport using machine learning.. We will create three machine