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Dominance and Efficiency in Multiobjective Stochastic Linear Programming

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Advances in Multiple Objective and Goal Programming

Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 455))

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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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Author information

Authors and Affiliations

  1. Institut Supérieur de Gestion, Le Bardo, 2000, Tunisia

    F. Ben Abdelaziz

  2. Faculté des Sicences de l’Administration, Université Laval, Ste Foy, Québec, Canada, G1K 7P4

    P. Lang & R. Nadeau

Authors
  1. F. Ben Abdelaziz
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  2. P. Lang
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  3. R. Nadeau
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Editor information

Editors and Affiliations

  1. Departamento de Economía Aplicada (Matemáticas) Facultad de Ciencias Económicas y Empresariales, University of Málaga, Campus El Ejido s/n, 29071, Málaga, Spain

    Rafael Caballero  & Francisco Ruiz  & 

  2. Faculty of Management Science, University of Georgia, 206 Brooks Hall, 30602-6255, Athens, Georgia, USA

    Ralph Steuer

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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

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63599-4

  • Online ISBN: 978-3-642-46854-4

  • eBook Packages: Springer Book Archive

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