Maximization of an Asymmetric Utility Function by the Least Squares
DOI:
https://doi.org/10.7494/dmms.2014.8.1.5Keywords:
individual behavior, inverse problems, simultaneous equations, optimizationAbstract
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
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Published
2014-11-19
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How to Cite
[1]
Yoneda, K. and Moretti, A.C. 2014. Maximization of an Asymmetric Utility Function by the Least Squares. Decision Making in Manufacturing and Services. 8, 1-2 (Nov. 2014), 5–12. DOI:https://doi.org/10.7494/dmms.2014.8.1.5.
Received 2013-10-25
Accepted 2014-09-09
Published 2014-11-19
Accepted 2014-09-09
Published 2014-11-19
