Solving the Extended Job Shop Scheduling Problem with AGVs -- Classical
  and Quantum Approaches
  The subject of Job Scheduling Optimisation (JSO) deals with the scheduling of
jobs in an organization, so that the single working steps are optimally
organized regarding the postulated targets. In this paper a use case is
provided which deals with a sub-aspect of JSO, the Job Shop Scheduling Problem
(JSSP or JSP). As many optimization problems JSSP is NP-complete, which means
the complexity increases with every node in the system exponentially. The goal
of the use case is to show how to create an optimized duty rooster for certain
workpieces in a flexible organized machinery, combined with an Autonomous
Ground Vehicle (AGV), using Constraint Programming (CP) and Quantum Computing
(QC) alternatively. The results of a classical solution based on CP and on a
Quantum Annealing model are presented and discussed. All presented results have
been elaborated in the research project PlanQK.
