Multi-objective multi-load tandem autonomous guided vehicle for robust workload balance and material handling optimization

Effective transportation methods in automated manufacturing systems increase efficiency and decrease final product cost. Flexibility of autonomous guided vehicles (AGVs) in performing transportation tasks makes them an important option in automated manufacturing system design. Optimal decisions for configuring tandem AGV system in a real-time mechanism are important. In this study, we propose a nonlinear binary mathematical model to configure a tandem AGV system, where multiple-load AGVs are considered. A multi-objective model has been developed to minimize inter- and intra-loop transportations and to balance workload in different cells based on AGVs performance. Since AGVs performance may change by considering different loading and unloading policies, robust optimization approach has been applied in modeling. Then, a hierarchical methodology has been proposed to solve the optimization problem. Finally, an illustrative example is developed to check the validity of the proposed mathematical model. Sensitivity analyses emphasize the contribution of the work and imply managerial implications for decision makers and policy developers.