Abstract
In contrast to deterministic multiobjective problems, where the notion of Pareto-efficiency is well accepted, several notions of efficiency are conceivable for the Multiobjective Stochastic Linear Programming problem. Their relevance depends on the available state of information about the decision situation, regarding particularly the Decision Maker’s preference structure and probabilistic anticipations. We investigate efficient sets arising naturally from some extreme reference cases of states of information. We study these sets from the point of view of their relative inclusions and provide some indications as to their computability.
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References
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© 1997 Springer-Verlag Berlin Heidelberg
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Ben Abdelaziz, F., Lang, P., Nadeau, R. (1997). Dominance and Efficiency in Multiobjective Stochastic Linear Programming. In: Caballero, R., Ruiz, F., Steuer, R. (eds) Advances in Multiple Objective and Goal Programming. Lecture Notes in Economics and Mathematical Systems, vol 455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46854-4_17
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DOI: https://doi.org/10.1007/978-3-642-46854-4_17
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