A fuzzy inference system to scheduling tasks in queueing systems

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Abstract

This paper studies the problem of scheduling customers or tasks in a queuing system. Generally the customers or a set of tasks in queuing system are attended according with different rules as round robin, equiprobable, shortest queue, among others. However, the condition of the system like the work in process, utilization and the length of queue is difficult to measure. We propose to use a fuzzy inference system in order to determine the status in the system depended of input variables like the length queue and the utilization. The experiment results shows an improvement in the performance measures compared with traditional scheduling policies.

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APA

López-Santana, E. R., Franco, C., & Figueroa-Garcia, J. C. (2017). A fuzzy inference system to scheduling tasks in queueing systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10363 LNAI, pp. 286–297). Springer Verlag. https://doi.org/10.1007/978-3-319-63315-2_25

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