Optimizing a priority-discipline queueing model using fuzzy set theory

被引:19
|
作者
Jose Pardo, Maria
de la Fuente, David
机构
[1] Univ Basque Country, Dept Appl Econ 4, Bilbao 48015, Spain
[2] Univ Oviedo, Dept Accounting & Business Adm, Gijon 33204, Spain
关键词
fuzzy subset theory; queueing theory; priority-discipline; fuzzy system model;
D O I
10.1016/j.camwa.2007.01.019
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The aim of this paper is to provide a more realistic description of priority-discipline queueing models by using Fuzzy Set Theory. It develops and optimizes two fuzzy queueing models with priority-discipline, a model with nonpreemptive priorities system and a model with preemptive priorities system, denoted by (M) over tilde (i)/(M) over tilde (i)/1 and (M) over tilde (i)/F-i/1. The first symbol is for a queueing system where arrivals and services from a single server follow a Poisson process with fuzzy parameter and the last symbol is for a queueing model with arrivals follows a Poisson process with fuzzy rate and fuzzy deterministic service rate. Zadeh's extension principle is the basic approach to this research into fuzzy stochastic processes. Our results are the basis for a discussion of optimal selection of priority-discipline. Two fuzzy queueing systems that are commonly found in real situations are solved, and serve as examples that highlight the validity of the procedure we propose. Fuzzy queueing models are more realistic than the crisp queues that are commonly used in reality. Furthermore, extending queueing models to the fuzzy environment widens their scope of application. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:267 / 281
页数:15
相关论文
共 50 条
  • [31] Fuzzy comprehensive evaluation model based on rough set theory
    Xu, Yitian
    Wang, Laisheng
    PROCEEDINGS OF THE FIFTH IEEE INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS, VOLS 1 AND 2, 2006, : 877 - 880
  • [32] Reformulating decision theory using fuzzy set theory and Shafer's theory of evidence
    Bordley, RF
    FUZZY SETS AND SYSTEMS, 2003, 139 (02) : 243 - 266
  • [33] Evaluation of Rolling Bearing Vibration Using Fuzzy Set Theory and Chaos Theory
    Sun, Xiaochao
    Xia, Xintao
    Liu, Yanbin
    Gao, Leilei
    ADVANCED RESEARCH ON ENGINEERING MATERIALS, ENERGY, MANAGEMENT AND CONTROL, PTS 1 AND 2, 2012, 424-425 : 338 - 341
  • [34] A generalized approach to students' evaluation using fuzzy set theory
    Zhang, Quan
    Gao, Qi-Sheng
    Zheng, Hai-Ying
    Liu, Wei-Dong
    DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2007, 14 : 888 - 892
  • [35] Using fuzzy set theory to address the uncertainty of susceptibility to drought
    Eierdanz, Frank
    Alcamo, Joseph
    Acosta-Michlik, Lilibeth
    Kroemker, Doerthe
    Taenzler, Dennis
    REGIONAL ENVIRONMENTAL CHANGE, 2008, 8 (04) : 197 - 205
  • [36] Using fuzzy set theory to address the uncertainty of susceptibility to drought
    Frank Eierdanz
    Joseph Alcamo
    Lilibeth Acosta-Michlik
    Dörthe Krömker
    Dennis Tänzler
    Regional Environmental Change, 2008, 8 : 197 - 205
  • [37] ESTIMATION OF POLYMER FLOODING USING A FUZZY SET-THEORY
    YEREMIN, NA
    SURINA, VV
    PRIKAZCHIKOVA, MS
    NEFTYANOE KHOZYAISTVO, 1994, (04): : 56 - 57
  • [38] Skidding Machines Allocation (SMA) Using Fuzzy Set Theory
    Ghajar, Esmael
    Najafi, Akbar
    Ezzati, Sattar
    CROATIAN JOURNAL OF FOREST ENGINEERING, 2010, 31 (02) : 99 - 110
  • [39] A new method for CBR prediction using fuzzy set theory
    Cuvalcioglu, Gokhan
    Taciroglu, Murat Vergi
    Bal, Arif
    CONSTRUCTION AND BUILDING MATERIALS, 2024, 447
  • [40] On-Line Signature Evaluation Using Fuzzy Set Theory
    Shin, Jungpil
    Kikuchi, Tomomi
    2013 IEEE 27TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS WORKSHOPS (WAINA), 2013, : 273 - 277