Simulation-based assessment of machine criticality measures for a shifting bottleneck scheduling approach in complex manufacturing systems

In this paper, we describe adaptation techniques for a hierarchically organized multi-agent-system (MAS) applied to production control of complex job shops. The system architecture of the production control system is based on three different control layers. The mid layer implements a distributed shifting bottleneck type solution procedure. The shifting bottleneck heuristic decomposes the overall scheduling problem into scheduling problems for parallel machines. The sequence of solving the resulting scheduling problems for parallel machines is determined by machine criticality measures. We can adapt this solution scheme in a situation dependent manner by choosing appropriate machine criticality measures. Furthermore, the performance of the shifting bottleneck scheme is also influenced by the selection of a proper subproblem solution procedure for each of the parallel machine scheduling problems. The subproblem solution procedures typically are given by heuristics. A situation dependent parameterization of these heuristics is highly desirable. In this paper, we sketch an overall concept for adaptation of our hierarchically organized multi-agent-system. We present results of computational experiments based on the simulation of a dynamic environment for the appropriate selection of machine criticality measures.