Solving fuzzy queueing decision problems via a parametric mixed integer nonlinear programming method [An article from: European Journal of Operational Research] | ![Solving fuzzy queueing decision problems via a parametric mixed integer nonlinear programming method [An article from: European Journal of Operational Research]](http://ecx.images-amazon.com/images/I/51G4P0G7AGL._SL160_.jpg)
 enlarge | Author: S.p. Chen
Publisher: Elsevier
Category: Book
Buy New: $7.95
Format: Html
Media: Digital
Publication Date: February 16, 2007
Availability: Available for download now
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Product Description
This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
This paper proposes a mathematical programming method to construct the membership functions of the fuzzy objective value of the cost-based queueing decision problem with the cost coefficients and the arrival rate being fuzzy numbers. On the basis of Zadeh's extension principle, three pairs of mixed integer nonlinear programs (MINLP) parameterized by the possibility level @a are formulated to calculate the lower and upper bounds of the minimal expected total cost per unit time at @a, through which the membership function of the minimal expected total cost per unit time of the fuzzy objective value is constructed. To provide a suitable optimal service rate for designing queueing systems, the Yager's ranking index method is adopted. Two numerical examples are solved successfully to demonstrate the validity of the proposed method. Since the objective value is completely expressed by a membership function rather than by a crisp value, it conserves the fuzziness of the input information, thus more information is provided for designing queueing systems. The successful extension of queueing decision models to fuzzy environments permits queueing decision models to have wider applications in practice.
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