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Abstract

This chapter is excerpted from ‘Operations Methods: Waiting Line Applications'. The intent of this monograph is to help business practitioners expand their knowledge of waiting line (queuing) analysis and how it can be used to make decisions and improve both service and manufacturing business situations. Readers are assumed to have some familiarity with using probability distributions and Excel analysis tools. Those wishing to refresh their knowledge are provided some brief reviews and references for doing so. Emphasis is given to discussing the caveats in applying waiting line theory and becoming aware of the assumptions used in developing that theory. The importance of accounting for variability in waiting line processes is discussed in some detail because the basic queuing equations provide only average performance data under steady-state conditions. Understanding how much variability can exist for a given waiting line scenario provides a manager with the insight required to reduce these effects and develop innovative solutions for improving service while reducing operating costs. In general the mathematical tone of the book is focused on application, not the derivation of the formulas presented. The few derivation exceptions are done to illustrate some approaches not commonly discussed in textbooks - for example, the use of state diagrams and random number approximations of the probability distributions for use in simple simulation models. To aid in understanding the material presented, some practical examples are given at appropriate points in the text and a few simulation approaches using common spreadsheet software are described.

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Abstract

This chapter is excerpted from ‘Operations Methods: Waiting Line Applications'. The intent of this monograph is to help business practitioners expand their knowledge of waiting line (queuing) analysis and how it can be used to make decisions and improve both service and manufacturing business situations. Readers are assumed to have some familiarity with using probability distributions and Excel analysis tools. Those wishing to refresh their knowledge are provided some brief reviews and references for doing so. Emphasis is given to discussing the caveats in applying waiting line theory and becoming aware of the assumptions used in developing that theory. The importance of accounting for variability in waiting line processes is discussed in some detail because the basic queuing equations provide only average performance data under steady-state conditions. Understanding how much variability can exist for a given waiting line scenario provides a manager with the insight required to reduce these effects and develop innovative solutions for improving service while reducing operating costs. In general the mathematical tone of the book is focused on application, not the derivation of the formulas presented. The few derivation exceptions are done to illustrate some approaches not commonly discussed in textbooks - for example, the use of state diagrams and random number approximations of the probability distributions for use in simple simulation models. To aid in understanding the material presented, some practical examples are given at appropriate points in the text and a few simulation approaches using common spreadsheet software are described.

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