An integrated analytical/simulation approach for economic design of an automated guided vehicle system

This paper proposes an integrated analytical/simulation approach for designing an automated guided vehicle system (AGVS) which consists of AGVs, machines with input buffers and a dispatching station in a just-in-time (JIT) environment. The objective is to determine the number of AGVs, the input buffer capacities and locations of the machines that minimize a cost function under the constraint that the planned utilization of each machine is achieved. The integrated analytical/simulation approach employs a simulation model to evaluate the performance of the AGVS and an analytical approach to reduce the repetition number of simulations in searching for an optimal solution. The analytical approach leads to an efficient iterative procedure based on monotonicity properties of the cost function and the machine utilization in each design factor, and lower bounds of the number of AGVs and the input buffer capacities. Moreover, initial locations of the machines are derived from the hierarchical location–prediction inequality. Computational results are given to demonstrate the efficiency of the proposed procedure. It is observed that the lower bounds and the initial locations are the optimal solution in case of deterministic processing times at machines.