Abstract
It is shown how to transform a stochastic linear programming problem (SLP) into an equivalent stochastic multiple criteria problem (SMC). Regarding rational decision making a solution to the SLP should be an efficient solution to the SMC. It is shown that the chance constrained programming problem can be derived from the SMC and that the corresponding solutions are efficient solutions. Considering different assumptions, another decision model is derived from the SMC. In this case an efficient solution is found with the aid of goal programming models. These models are analysed with respect to convexity properties of the objective function, considering normal or uniform distribution.
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© 1985 Springer-Verlag Berlin Heidelberg
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Gal, T., Wolf, H. (1985). Solving Stochastic Linear Programms Via Goal Programming. In: Haimes, Y.Y., Chankong, V. (eds) Decision Making with Multiple Objectives. Lecture Notes in Economics and Mathematical Systems, vol 242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46536-9_6
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DOI: https://doi.org/10.1007/978-3-642-46536-9_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-15223-1
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