Stochastic goal programming: A mean–variance approach

We propose a stochastic goal programming (GP) model leading to a structure of mean–variance minimisation. The solution to the stochastic problem is obtained from a linkage between the standard expected utility theory and a strictly linear, weighted GP model under uncertainty. The approach essentiall...

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Published in:European journal of operational research 2001-06, Vol.131 (3), p.476-481
Main Author: Ballestero, Enrique
Format: Article
Language:English
Subjects:
Expected utility
Expected utility theory
Goal programming
Stochastic models
Studies
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description We propose a stochastic goal programming (GP) model leading to a structure of mean–variance minimisation. The solution to the stochastic problem is obtained from a linkage between the standard expected utility theory and a strictly linear, weighted GP model under uncertainty. The approach essentially consists in specifying the expected utility equation corresponding to every goal. Arrow's absolute risk aversion coefficients play their role in the calculation process. Once the model is defined and justified, an illustrative example is developed.
doi_str_mv 10.1016/S0377-2217(00)00084-9
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ispartof European journal of operational research, 2001-06, Vol.131 (3), p.476-481
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source ScienceDirect Journals
subjects Expected utility
Expected utility theory
Goal programming
Stochastic models
Studies
title Stochastic goal programming: A mean–variance approach
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