Scheduling of Mobile Robots Using Constraint Programming

Abstract

Mobile robots in flexible manufacturing systems can transport components for jobs between machines as well as process jobs on selected machines. While the job shop problem with transportation resources allows encapsulating of transportation, this work concentrates on the extended version of the problem, including the processing by mobile robots. We propose a novel constraint programming model for this problem where the crucial part of the model lies in a proper inclusion of the transportation. We have implemented it in the Optimization Programming Language using the CP Optimizer, and compare it with the existing mixed integer programming solver. While both approaches are capable of solving the problem optimally, a new constraint programming approach works more efficiently, and it can compute solutions in more than an order of magnitude faster. Given that, the results of more realistic data instances are delivered in real-time, which is very important in a smart factory.