Maximization of an Asymmetric Utility Function by the Least Squares

• Autorzy: Kiyoshi Yoneda , Antonio Carlos Moretti
• Języki publikacji: EN

Abstrakty

EN

This note points out that a utility maximization procedure proposed in an earlier paper may be reduced to the least squares. The utility function is asymmetric in the sense that for each cue its ideal value and the permissible range are assigned in such a way that the ideal is not necessarily at the center of the range, like "a beer of 350 ml would be ideal, but acceptable if within [100, 500]". A practical consequence of the observation is that very little programming will be needed to deploy the utility maximization since software for the least squares is widely available. (original abstract)

Słowa kluczowe

EN

Algorithms; Least squares method; Decision making; Optimalization

PL

Algorytmy; Metoda najmniejszych kwadratów; Podejmowanie decyzji; Optymalizacja

• Czasopismo: Decision Making in Manufacturing and Services
• Rocznik: 2014
• Tom: 8
• Numer: nr 1/2
• Strony: 5--12

Twórcy

autor

Kiyoshi Yoneda

• Fukuoka University

autor

Antonio Carlos Moretti

• School of Applied Sciences State University of Campinas-SP, Brazil

Bibliografia

• Hastie, R., Dawes, R.M., 2009. Rational Choice in an Uncertain World: The Psychology of Judgement and Decision Making, 2nd Edition. Sage Publications, Inc.
• R Core Team, 2013. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/
• Turi, D., 2001. Category Theory Lecture Notes. University of Edinburgh. URL http://www.dcs.ed.ac.uk/home/dt/CT/categories.pdf
• Yoneda, K., Celaschi, W., 2013. A utility function to solve approximate linear equations for decision making. Decision Making in Manufacturing and Services, 7(1-2), pp. 5-18. URL http://www.dmms.agh.edu.pl/Volume_7/DMMS_2013_Yoneda_Celaschi.pdf

Identyfikatory

DOI

10.7494/dmms.2014.8.1.5