University of Maryland

Allocating Samples for Selection Decisions with Multiple Uncertain Attributes

This page contains the following sections:

Background
Publications

Research Team: Dennis D. Leber, National Institute of Standards and Technology, and Jeffrey W. Herrmann, University of Maryland.

Background

This research project is studying the collection of information for multiple attribute (multiple-criteria) selection problems.

In some cases, a decision-maker has a limited budget to collect data (samples) that will be used to analyze a multiple attribute selection decision. Because the sampling (measurement) process has uncertainty, more samples provide better information, but each sample can measure only one attribute of one alternative. With a limited budget, determining the number of samples to observe from each alternative and attribute is an critical information gathering decision. We have developed and tested multiple approaches to determine which approaches maximize the probability of selecting the true best alternative.

This research is generating knowledge about the performance of sample allocation schemes for multiple attribute (multiple-criteria) selection problems.

Related Publications

Leber, Dennis D., and J.W. Herrmann, Incorporating Attribute Value Uncertainty into Decision Analysis, Proceedings of the 2012 Industrial and Systems Engineering Research Conference, Orlando, Florida, May 20-22, 2012.
Leber, Dennis D., and J.W. Herrmann, Allocating Attribute-Specific Information-Gathering Resources To Improve Selection Decisions, Proceedings of the 2013 Winter Simulation Conference, R. Pasupathy, S.-H. Kim, A. Tolk, R. Hill, and M. E. Kuhl, eds., Washington, D.C., December 8-11, 2013.
Leber, Dennis D., and J.W. Herrmann, Decision Analysis Methods for Selecting Consumer Services with Attribute Value Uncertainty, in Risk Assessment and Evaluation of Predictions, M.-L. T. Lee, M. Gail, R. Pfeiffer, G. Satten, T. Cai, and A. Gandy, editors, Lecture Notes in Statistics, Volume 210, pages 405-424, Springer, New York, 2013.
Leber, Dennis D., and J.W. Herrmann, Resource Allocation for Selection Decisions with Measurement Uncertainty, Proceedings of the 2014 Industrial and Systems Engineering Research Conference, Y. Guan and H. Liao, eds., Montreal, Canada, June 1-3, 2014.
Leber, Dennis D., and J.W. Herrmann, Sample Allocation for Multiple Attribute Selection Problems, Proceedings of the 2014 Winter Simulation Conference, A. Tolk, S.D. Diallo, I.O. Ryzhov, L. Yilmaz, S. Buckley, and J.A. Miller, eds., Savannah, Georgia, December 7-10, 2014.
Leber, Dennis, and J.W. Herrmann, Impact of Decision and Allocation Rules on Selection Decision Quality, Industrial and Systems Engineering Research Conference, Nashville, Tennessee, May 30-June 2, 2015.
Leber, Dennis D., and Jeffrey W. Herrmann, Sequential Sample Allocation for Multiple Attribute Selection Decisions, Proceedings of the 2016 Industrial and Systems Engineering Research Conference, H. Yang, Z. Kong, and MD Sarder, eds., Anaheim, California, May 22-25, 2016.
Leber, Dennis D., Optimal Budget-Constrained Sample Allocation for Selection Decisions with Multiple Uncertain Attributes, dissertation, University of Maryland, College Park, 2016.

Last updated on August 5, 2016, by Jeffrey W. Herrmann.