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An Efficient Technique for Solving Fully Fuzzified Multiobjective Stochastic Programming Problems

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Information Systems Design and Intelligent Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 339))

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Abstract

This paper develops a fuzzy programming technique for solving multiobjective stochastic programming problems having right side parameters associated with the system constraints follow exponential distribution. In the model formulation process the coefficients of the objectives as well as the system constraints are taken as fuzzy numbers. The variables are also considered as fuzzy variables. In the proposed solution process the probabilistic problem is first converted into an equivalent fuzzy programming model applying chance constrained programming methodology. Then using the concept of ranking function the problem is transferred into an equivalent deterministic model. The individual optimal value of each objective is found in isolation to construct the membership goals of the objectives. Finally fuzzy goal programming approach is used for achieving the best compromise solution to the extent possible in the decision making context. An illustrative numerical example is given to demonstrate the efficiency of the proposed methodology.

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Acknowledgments

The authors are thankful to the anonymous reviewers for their valuable comments and suggestions in improving the quality of the paper.

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Authors and Affiliations

  1. Department of Mathematics, University of Kalyani, Kalyani, 741235, India

    Animesh Biswas

  2. Department of Mathematics, Academy of Technology, G.T.Road, Adisaptagram, Aedconagar, Hooghly, 712121, India

    Arnab Kumar De

Authors
  1. Animesh Biswas
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  2. Arnab Kumar De
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Corresponding author

Correspondence to Animesh Biswas .

Editor information

Editors and Affiliations

  1. University of Kalyani, Kalyani, West Bengal, India

    J. K. Mandal

  2. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Vishakapatnam, India

    Suresh Chandra Satapathy

  3. Dean, Faculty of Engineering, Technology, University of Kalyani, Kalyani, West Bengal, India

    Manas Kumar Sanyal

  4. Engineering and Technological Studies, University of Kalyani, Kalyani, West Bengal, India

    Partha Pratim Sarkar

  5. Department Computer Science & Engineering, University of Kalyani, Kalyani, India

    Anirban Mukhopadhyay

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Biswas, A., De, A.K. (2015). An Efficient Technique for Solving Fully Fuzzified Multiobjective Stochastic Programming Problems. In: Mandal, J., Satapathy, S., Kumar Sanyal, M., Sarkar, P., Mukhopadhyay, A. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 339. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2250-7_49

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  • DOI: https://doi.org/10.1007/978-81-322-2250-7_49

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2249-1

  • Online ISBN: 978-81-322-2250-7

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