Material handling equipment selection using multi-attribute utility theory and Monte Carlo simulation

The material handling equipment selection process can be classified as a multi-criteria decision ma_king problem because it involves multiple feasible alternatives and conflicting objectives. This paper utilizes multi-attribute utility theory and Monte Carlo simulation to select the most efficient Material Handling Equipment (MHE) for a manufacturing facility. The three main criteria, developed based on a material handling equation that involves a set of questions, are the material to be moved, the attributes of the move, and the means utilized for the move. By decomposing the three main criteria, a hierarchy of the sub-criteria is developed. The multi-attribute utility theory is used to model the decision maker's preferred judgments with consideration to the risk attitude. The utilities for individual attributes are determined and then aggregated using multiplicative utility functions. Monte Carlo simulation is used to capture the uncertainty associated with a single point estimate of the decision maker's preferred judgment, since it is treated as a random variable with a triangular distribution. The proposed approach is implemented in a small pharmaceutical company to select the MHE for the finished product inventory.