A multiple attribute utility theory approach to ranking and selection

Managers of large industrial projects often measure performance by multiple attributes. For example, our paper is motivated by the simulation of a lar ge industrial project called a land seismic survey, in which project perfor mance is based on duration, cost, and resource utilization. To address thes e types of problems, we develop a ranking and selection procedure for makin g comparisons of systems (e.g., project configurations) that have multiple performance measures. The procedure combines multiple attribute utility the ory with statistical ranking and selection to select the best configuration from a set of possible configurations using the indifference-zone approach . We apply our procedure to results generated by the simulator for a land s eismic survey that has six performance measures, and describe a particular type of sensitivity analysis that can be used as a robustness check.