Sample Allocation for Multiple Attribute Selection Problems
Dennis D. Leber, Jeffery W. Herrmann
Prior to making a multiple attribute selection decision, a decision-maker may collect information to estimate the value of each attribute for each alternative. In this work, we consider a fixed experimental sample budget and address the problem of how best to allocate this budget across three attributes when the attribute value estimates have a normally distributed measurement error. We illustrate that the allocation choice impacts the decision-makers ability to select the true best alternative. Through a simulation study we evaluate the performance of a common allocation approach of uniformly distributing the sample budget across the three attributes. We compare these results to the performance of several allocation rules that leverage the decision-makers preferences. We found that incorporating the decision-makers preferences, as well as knowledge about the characteristics of the alternatives, into the allocation choice improves the probability of selecting the true best alternative.
December 7-10, 2014
Proceedings of the 2014 Winter Simulation Conference
and Herrmann, J.
Sample Allocation for Multiple Attribute Selection Problems, Proceedings of the 2014 Winter Simulation Conference, Savannah, GA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=916091
(Accessed February 28, 2024)