A fuzzy inference system to scheduling tasks in queueing systems

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

Research output: Chapter in Book/ReportConference contribution

2 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationIntelligent Computing Methodologies - 13th International Conference, ICIC 2017, Proceedings
EditorsAbir Hussain, Kyungsook Han, De-Shuang Huang, M. Michael Gromiha
Number of pages12
ISBN (Print)9783319633145
StatePublished - 2017
Event13th International Conference on Intelligent Computing, ICIC 2017 - Liverpool, United Kingdom
Duration: Aug 7 2017Aug 10 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10363 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference13th International Conference on Intelligent Computing, ICIC 2017
Country/TerritoryUnited Kingdom

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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