Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization.

ABSTRACT: Flexible manufacturing system (FMS) enhances the firm's flexibility and responsiveness to the ever-changing customer demand by providing a fast product diversification capability. Performance of an FMS is highly dependent upon the accuracy of scheduling policy for the components of the system, such as automated guided vehicles (AGVs). An AGV as a mobile robot provides remarkable industrial capabilities for material and goods transportation within a manufacturing facility or a warehouse. Allocating AGVs to tasks, while considering the cost and time of operations, defines the AGV scheduling process. Multi-objective scheduling of AGVs, unlike single objective practices, is a complex and combinatorial process. In the main draw of the research, a mathematical model was developed and integrated

SUBMITTER: Mousavi M 

PROVIDER: S-EPMC5338791 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature