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Fuzzy Number Linear Programming: A Probabilistic Approach

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Advances in Soft Computing — AFSS 2002 (AFSS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2275))

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Abstract

In real world there are many problems which have linear programming models where all decision parameters are fuzzy numbers. There are some approaches which are using different ranking functions for solving these problems. Unfortunately all these methods when there exist alternative optimal solutions, usually with different fuzzy value of the objective function for these solutions, can not specify a clear approach for choosing a solution. In this paper using the concept of expectation and variance as ranking functions, we propose a method to remove the above shortcomings in solving fuzzy number linear programming problems.

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References

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Author information

Authors and Affiliations

  1. Faculty of Math. and Computer Sciences, Kerman University, Kerman, Iran

    Hamid Reza Maleki & Mashaallah Mashinchi

  2. Department of Mathematics, Sistan and Baluchestan university, Zahedan, Iran

    N. Hassan Mishmast

Authors
  1. Hamid Reza Maleki
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  2. N. Hassan Mishmast
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  3. Mashaallah Mashinchi
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Editor information

Editors and Affiliations

  1. Electronics and Communication Sciences Unit, Indian Statistical Institute, 203 B.T. Road, 700108, Calcutta, India

    Nikhil R. Pal

  2. Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako, Japan

    Michio Sugeno

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© 2002 Springer-Verlag Berlin Heidelberg

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Maleki, H.R., Mishmast, N.H., Mashinchi, M. (2002). Fuzzy Number Linear Programming: A Probabilistic Approach. In: Pal, N.R., Sugeno, M. (eds) Advances in Soft Computing — AFSS 2002. AFSS 2002. Lecture Notes in Computer Science(), vol 2275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45631-7_67

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  • DOI: https://doi.org/10.1007/3-540-45631-7_67

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43150-3

  • Online ISBN: 978-3-540-45631-5

  • eBook Packages: Springer Book Archive

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