Simulation of fuzzy inference system to task scheduling in queueing networks

Eduyn Ramiro López-Santana, Carlos Franco-Franco, Juan Carlos Figueroa-García

Research output: Chapter in Book/ReportConference contribution

1 Scopus citations


This paper presents a simulation approach of the problem of scheduling customers in a queuing networks using a fuzzy inference system. Usually, in the queuing systems there are rules as round robin, equiprobable, shortest queue, among others, to schedule customers, however the condition of the system like the cycle time, utilization and the length of queue is difficult to measure. We propose a fuzzy inference system in order to determine the status in the system using input variables like the length queue and utilization. Our simulation shows an improvement in the performance measures compared with traditional scheduling policies.

Original languageEnglish (US)
Title of host publicationApplied Computer Sciences in Engineering - 4th Workshop on Engineering Applications, WEA 2017, Proceedings
EditorsJuan Carlos Figueroa-Garcia, Eduyn Ramiro Lopez-Santana, Roberto Ferro-Escobar, Jose Luis Villa-Ramirez
Number of pages12
ISBN (Print)9783319669625
StatePublished - 2017
Externally publishedYes
Event4th Workshop on Engineering Applications, WEA 2017 - Cartagena, Colombia
Duration: Sep 27 2017Sep 29 2017

Publication series

NameCommunications in Computer and Information Science
ISSN (Print)1865-0929


Conference4th Workshop on Engineering Applications, WEA 2017

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Mathematics


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