Estimating the form of a decision maker’s preference function and converging towards preferred solutions

Gülşah Karakaya and Murat Köksalan

IISE Transactions, 2020, vol. 52, issue 6, 651-664

Abstract: Preference functions have been widely used to scalarize multiple objectives. Various forms such as linear, quasiconcave, or general monotone have been assumed. In this article, we consider a general family of functions that can take a variety of forms and has properties that allow for estimating the form efficiently. We exploit these properties to estimate the form of the function and converge towards a preferred solution(s). We develop the theory and algorithms to efficiently estimate the parameters of the function that best represent a decision maker’s preferences. This in turn facilitates fast convergence to preferred solutions. We demonstrate on a variety of experiments that the algorithms work well both in estimating the form of the preference function and converging to preferred solutions.

Date: 2020
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DOI: 10.1080/24725854.2019.1670373

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