Simultaneous workload balancing and travel time minimization of automatic guided vehicles

Abstract

This paper presents the application of a novel modified memetic particle swarm optimization algorithm (MMPSO) for simultaneous workload balancing and travel time minimization of automatic guided vehicles (AGVs) in the flexible manufacturing system (FMS). Three FMS layouts consisting of 5; 7 and 9 work centers are considered respectively for the simultaneous scheduling of AGVs in the FMS layouts. The resulting yield from the MMPSO algorithm is compared with the resulting yield of other implemented methods. From the results, it is observed that the application of the MMPSO algorithm outperforms the other applied algorithms from the literature. It was also observed that by the application of MMPSO algorithm a balanced exploration and exploitation of solutions can be achieved for the simultaneous scheduling of AGVs in the FMS.