Heuristic approaches for scheduling jobs and vehicles in a cyclic flexible manufacturing system.

Abstract This paper addresses the scheduling of automated guided vehicles (AGVs) in a cyclic flexible flow shop environment. The vehicles travel along a single loop. All production machines are located alongside the track in the required order, with a possibility for multiple machines per stage. All AGVs are to be scheduled for a specific starting time and will then continuously circle the track. Pickup and delivery times are included in the travel time of a vehicle, stops are forbidden. Jobs may start upon arrival if their predecessor has been started for processing. Therefore, job completion times are dynamic. The considered objectives are the minimization of the number of AGVs and of the total makespan. For the regarded problem, different local search variants are proposed. Optimal results are produced using a brute force enumeration algorithm. Finally, fixed permutation schedules are compared to processing jobs according to a first-come-first-serve rule.