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Fuzzy Cost Computations of M/M/1 and M/G/1 Queueing Models

机译:M / M / 1和M / G / 1排队模型的模糊成本计算

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In this paper two models of planning queuing system and its effect on the cost of the each system by using two fuzzy queuing models of M/M/1 and M/G/1 are studied. These two fuzzy queuing models based on the cost of each model are compared and fuzzy ranking methods are used to select the optimal model due to the resulted complexity. Fuzzy queuing is more practical and realistic than deterministic queuing models. The basic idea is to transform a fuzzy queuing cost problem to a family of conventional crisp queue cost problem by applying the α-cut approach and Zadeh’s extension principle. A set of parametric nonlinear programs are developed to calculate the lower and upper bound of the minimal expected total cost per unit time at α, through which the membership function of the total cost is constructed. Numerical example is illustrated to check the validity of the proposed method.
机译:本文利用M / M / 1和M / G / 1两种模糊排队模型,研究了两种计划排队系统模型及其对每个系统成本的影响。比较了基于每个模型成本的这两个模糊排队模型,并由于结果复杂性,使用模糊排序方法来选择最佳模型。模糊排队比确定性排队模型更实际和现实。基本思想是通过应用α割方法和Zadeh的扩展原理,将模糊排队成本问题转化为一系列常规的明晰排队成本问题。开发了一组参数非线性程序来计算单位时间最小期望总成本在α处的上下限,从而构造总成本的隶属函数。数值例子说明了该方法的有效性。

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