Production flows scheduling subject to fuzzy processing time constraints

Effective sequencing and scheduling of material handling systems (MHSs) have a major impact on the productivity of a manufacturing system. Since the main function of a MHS is to supply the right materials at the right locations at the right time, the design of automated guided vehicles (AGVs) fleet-oriented, distributed and scalability-robust control policies ensuring deadlock-free operations is of crucial importance. In this context, a given design of a flexible manufacturing system (FMS) where vehicles serve workstations located along different modes of cyclic guided paths in a 3D environment composed of rails/lifts/hoists is considered. Furthermore, fuzzy processing time constraints on transportation operations, a production flows scheduling problem subject to an assumed set of constraints imposed by admissible production routes and schedules of AGV fleet in a given MHS are considered. Since this type of problem can be treated as a fuzzy constraint satisfaction problem, the main objective is to provide analytical formulas enabling the avoidance of time-consuming computer-simulation-based calculations of AGV fleet schedules, as well as vehicles deadlock and collisions, while keeping the throughput at the maximum achievable level. Results of computational experiments assessing the scalability of the proposed method are presented as well.