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Extremization of multi-objective stochastic fractional programming problem

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  • V. Charles
  • D. Dutta

Abstract

This paper addresses classes of assembled printed circuit boards, which faces certain kinds of errors during its process of manufacturing. Occurrence of errors may lead the manufacturer to be in loss. The encountered problem has two objective functions, one is fractional and the other is a non-linear objective. The manufacturers are confined to maximize the fractional objective and to minimize the non-linear objective subject to stochastic and non-stochastic environment. This problem is decomposed into two problems. A solution approach to this model has been developed in this paper. Results of some test problems are provided. Copyright Springer Science + Business Media, Inc. 2006

Suggested Citation

  • V. Charles & D. Dutta, 2006. "Extremization of multi-objective stochastic fractional programming problem," Annals of Operations Research, Springer, vol. 143(1), pages 297-304, March.
  • Handle: RePEc:spr:annopr:v:143:y:2006:i:1:p:297-304:10.1007/s10479-006-7389-7
    DOI: 10.1007/s10479-006-7389-7
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    References listed on IDEAS

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    1. Dutta, D. & Rao, J. R. & Tiwari, R. N., 1993. "A restricted class of multiobjective linear fractional programming problems," European Journal of Operational Research, Elsevier, vol. 68(3), pages 352-355, August.
    2. Stanley Zionts, 1968. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 15(3), pages 449-451, September.
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    Cited by:

    1. Charles, V. & Udhayakumar, A. & Rhymend Uthariaraj, V., 2010. "An approach to find redundant objective function(s) and redundant constraint(s) in multi-objective nonlinear stochastic fractional programming problems," European Journal of Operational Research, Elsevier, vol. 201(2), pages 390-398, March.
    2. Charles, Vincent & Kumar, Mukesh & Irene Kavitha, S., 2012. "Measuring the efficiency of assembled printed circuit boards with undesirable outputs using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 136(1), pages 194-206.

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