A Greedy Randomized Adaptive Search Procedure based Scheduling Algorithm for Flexible Manufacturing Systems with Multi-fixturing Pallets

Abstract

This study considers an operations scheduling problem for flexible manufacturing systems with multifixturing pallets that can load multiple parts. The problem is to determine the parts to be loaded on each pallet, i.e. palletizing, the input sequence of pallets to be initially released into the system, i.e. pallet input sequencing, the route of each pallet through machines, i.e. pallet routing, and the sequence of pallets to process the loaded parts on each machine, i.e. pallet process sequencing, for the objective of minimizing makespan. Practical constraints such as central buffer capacity, limited number of pallets and setup worker availability are considered. For a given set of pallets released into the central buffer, the pallet routing and process sequencing sub-problems can be regarded as an open shop scheduling problem. Based on this property, a two-stage heuristic approach is proposed in which pallet routing/input sequencing is done using a priority rule and the pallet routing/process sequencing sub-problems are repeatedly solved in an integrated way using a greedy randomized adaptive search procedure based algorithm. Computational experiments were done on a number of test instances and the results show that the two-stage approach outperforms the existing one significantly.