SENECA
Development of a self-learning decision support system for real-time job sequence and machine allocation planning
The research project SENECA aims at the development of a self-learning decision support system for real-time capable job sequence and machine allocation planning. The central research question is how machine learning (ML) methods have to be applied to compute in real-time acceptable solutions with sufficient quality for job sequence and machine allocation problems.
Weekly Jour Fixe
28.01.2021 -
Despite strict Covid19 requirements, the project team is constantly working on the SENECA project. Attached is a screenshot from the weekly Jour Fixe.
Publication submitted
13.01.2021 -
A Paper for the INCOM 2021 conference of the International Federation of Automatic Control (IFAC) has been submitted.
Project progress
09.09.2020 -
The project team is currently working on sub-project 2 "Conception and software implementation".
