Allocating Attribute-Specific Information-Gathering Resources to Improve Selection Decisions

Published

December 8, 2013

Author(s)

Dennis D. Leber, Jeffery W. Herrmann

Abstract

When collecting data to select an alternative from a finite set of alternatives that are described by multiple attributes, one must allocate effort to activities that provide information about the value of each attribute. This is a particularly relevant problem when the attribute values are estimated using experimental data. This paper discusses the problem of allocating an experimental budget amongst two attributes when the non-dominated decision alternatives form a concave efficient frontier. The results of a simulation study suggested allocation rules that take advantage of knowledge of the decision model and, when available, knowledge about the general shape of the frontier. These rules were compared to a default rule that equally allocated the experimental budget across the attributes. A proportional rule that allocated samples based on the value function weights performed well only in some cases; a more sophisticated step rule increased the frequency of correct selection across all weights.

Proceedings Title

Proceedings of the 2013 Winter Simulation Conference

Conference Dates

December 8-11, 2013

Conference Location

Washington, DC

Pub Type

Conferences

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Keywords

Proceedings of the 2013 Winter Simulation Conference Decision Analysis, Sample Allocation, Experiment Design, Attribute Value Uncertainty.

Citation

Leber, D. and Herrmann, J. (2013), Allocating Attribute-Specific Information-Gathering Resources to Improve Selection Decisions, Proceedings of the 2013 Winter Simulation Conference, Washington, DC, -1, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=913907 (Accessed October 9, 2025)