PROMISE: A DSS for multiple objective stochastic linear programming problems |
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Authors: | Raymond Nadeau Bruno Urli Laszlo N. Kiss |
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Affiliation: | (1) Sciences de l'administration, Université Laval, Québec, Canada;(2) Université du Québec à Rimouski, Québec, Canada |
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Abstract: | Most of the multiple objective linear programming (MOLP) methods which have been proposed in the last fifteen years suppose deterministic contexts, but because many real problems imply uncertainty, some methods have been recently developed to deal with MOLP problems in stochastic contexts. In order to help the decision maker (DM) who is placed before such stochastic MOLP problems, we have built a Decision Support System called PROMISE. On the one hand, our DSS enables the DM to identify many current stochastic contexts: risky situations and also situations of partial uncertainty. On the other hand, according to the nature of the uncertainty, our DSS enables the DM to choose the most appropriate interactive stochastic MOLP method among the available methods, if such a method exists, and to solve his problem via the chosen method. |
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Keywords: | Multiple objective linear programming stochastic decision support system |
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