Maximization of an Asymmetric Utility Function by the Least Squares

Authors

  • Kiyoshi Yoneda Fukuoka University
  • Antonio Carlos Moretti State University of Campinas

DOI:

https://doi.org/10.7494/dmms.2014.8.1.5

Keywords:

individual behavior, inverse problems, simultaneous equations, optimization

Abstract

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 an ideal value and a permissible range are assigned in such a way that the ideal value is not necessarily at the center of the interval, 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.

References

Hastie, Hastie, and Dawes] Hastie, R., Hastie, R., Dawes, R., Jun. 2001. Rational Choice in an Uncertain World: The Psychology of Judgement and Decision Making, 2nd Edition. Sage Pubn Inc. URL http://www.amazon.com/exec/obidos/redirect?tag= citeulike07-20&path=ASIN/076192275X

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. To be published. URL http://www.dmms.agh.edu.pl/Volume_7/DMMS_2013_Yoneda_ Celaschi.pdf

Downloads

Published

2014-11-19

How to Cite

Yoneda, K., & Moretti, A. C. (2014). Maximization of an Asymmetric Utility Function by the Least Squares. Decision Making in Manufacturing and Services, 8(1-2), 5–12. https://doi.org/10.7494/dmms.2014.8.1.5

Issue

Section

Articles