Allocating Attribute-Specific Information-Gathering Resources to Improve Selection Decisions
Dennis D. Leber, Jeffery W. Herrmann
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 of the 2013 Winter Simulation Conference
and Herrmann, J.
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 February 26, 2024)