Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

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-maker’s 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-maker’s preferences. We found that incorporating the decision-maker’s preferences, as well as knowledge about the characteristics of the alternatives, into the allocation choice improves the probability of selecting the true best alternative.
Conference Dates
December 7-10, 2014
Conference Location
Savannah, GA
Conference Title
Proceedings of the 2014 Winter Simulation Conference


Ranking and selection, experimental design, simulation, multicriteria decision making, decision analysis


Leber, D. and Herrmann, J. (2014), Sample Allocation for Multiple Attribute Selection Problems, Proceedings of the 2014 Winter Simulation Conference, Savannah, GA, [online], (Accessed July 13, 2024)


If you have any questions about this publication or are having problems accessing it, please contact

Created December 10, 2014, Updated January 27, 2020