In this paper, investigations are carried out for the multi-objective scheduling of AGVs to simultaneously balance the workload of AGVs and to minimize the travel time of AGVs in the FMS. | The scheduling of automatic guided vehicles for the workload balancing and travel time minimization in the flexible manufacturing system by the nature-inspired algorithm Journal of Project Management 4 2019 19 30 Contents lists available at GrowingScience Journal of Project Management homepage The scheduling of automatic guided vehicles for the workload balancing and travel time mini- mization in the flexible manufacturing system by the nature-inspired algorithm . Chawlaa A. K. Chandab and Surjit Angrac a Indira Gandhi Delhi Technical University For Women India b Engineering College India c Natioanl Institute of Technlogy Kurukshetra Haryana India CHRONICLE ABSTRACT Article history The real-time scheduling of automatic guided vehicles AGVs in flexible manufacturing system Received June 10 2018 FMS is observed to be highly critical and complex due to the dynamic variations of production Received in revised format July 1 requirements such as an imbalance of AGVs loading the high travel time of AGVs variation in 2018 jobs and AGV routes to name a few. The output from FMS considerably depends on the effi- Accepted August 2 2018 Available online cient scheduling of AGVs in the FMS. The multi-objective scheduling decisions for AGVs by August 3 2018 nature inspired algorithms yield a considerable reduction throughput time in the FMS. In this Keywords paper investigations are carried out for the multi-objective scheduling of AGVs to simultane- Automatic guided vehicles ously balance the workload of AGVs and to minimize the travel time of AGVs in the FMS. The Flexible manufacturing system multi-objective scheduling is carried out by the application of nature-inspired grey wolf optimi- Grey wolf optimization algorithm zation algorithm GWO to yield a balanced work-load for AGVs and also to minimize the travel Simultaneous scheduling time of AGVs simultaneously in the FMS. The output yield of the GWO algorithm is compared with the results .
