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

KARAKAYA G., Koksalan M.

IISE TRANSACTIONS, vol.52, no.6, pp.651-664, 2020 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 52 Issue: 6
  • Publication Date: 2020
  • Doi Number: 10.1080/24725854.2019.1670373
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.651-664
  • Keywords: Multiple objective programming, interactive algorithm, preference function form, QUASI-CONCAVE, MULTIPLE, CONVEX


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.