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Fuzzy Multiobjective Linear Programming: A Bipolar View

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Advances in Computational Intelligence (IPMU 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 300))

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Abstract

The traditional frameworks for fuzzy linear optimization problems are inspired by the max-min model proposed by Zimmermann using the Bellman-Zadeh extension principle. This paper attempts to view fuzzy multiobjective linear programming problem (FMOLPP) from a perspective of preference modeling. The fuzzy constraints are viewed as negative preferences for rejecting what is unacceptable while the objective functions are viewed as positive preferences for depicting satisfaction to what is desired. This bipolar view enable us to handle fuzzy constraints and objectives separately and help to combine them in distinct ways. The optimal solution of FMOLPP is the one which maximizes the disjunctive combination of the weighted positive preferences provided it satisfy the negative preferences combined in conjunctive way.

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Authors and Affiliations

  1. Department of Mathematics, Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India

    Dipti Dubey & Aparna Mehra

Authors
  1. Dipti Dubey
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  2. Aparna Mehra
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Editor information

Editors and Affiliations

  1. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco  & Benedetto Matarazzo  & 

  2. CNRS UMR 7606, DAPA, LIP6 8, Université Pierre et Marie Curie - Paris6, rue du Capitaine Scott, F-75015, Paris, France

    Bernadette Bouchon-Meunier

  3. Dip. Matematica e Informatica, Università di Perugia, 06123, Perugia, Italy

    Giulianella Coletti

  4. Department of Computer and Management Science, University of Trento, Via Inama 5, 38122, Trento, Italy

    Mario Fedrizzi

  5. Machine Intelligence Institute — IONA College,, 10801, New Rochelle, NY, USA

    Ronald R. Yager

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© 2012 Springer-Verlag Berlin Heidelberg

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Dubey, D., Mehra, A. (2012). Fuzzy Multiobjective Linear Programming: A Bipolar View. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 300. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31724-8_48

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  • DOI: https://doi.org/10.1007/978-3-642-31724-8_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31723-1

  • Online ISBN: 978-3-642-31724-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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