Compromise programming with Tchebycheff norm for discrete stochastic orders

Compromise programming with Tchebycheff norm for discrete stochastic orders

0.00 Avg rating0 Votes
Article ID: iaor2014116
Volume: 211
Issue: 1
Start Page Number: 433
End Page Number: 446
Publication Date: Dec 2013
Journal: Annals of Operations Research
Authors:
Keywords: compromise programming, decision trees, stochastic dominance, lotteries
Abstract:

This paper presents a method of decision making with returns in the form of discrete random variables. The proposed method is based on two approaches: stochastic orders and compromise programming used in multi‐objective programming. Stochastic orders are represented by stochastic dominance and inverse stochastic dominance. Compromise programming uses the augmented Tchebycheff norm. This norm, in special cases, takes form of the Kantorovich and Kolmogorov probability metrics. Moreover, in the paper we show applications of the presented methodology in the following problems: projects selections, decision tree and choosing a lottery.

Reviews

Required fields are marked *. Your email address will not be published.