Abstract
In the article the problem of design optimization maintenance schedule queue of applications is considered. The analysis of the main features of queuing systems is carried out. A modified evolutionary algorithm of plotting service applications is developed. The authors suggested a new approach on the basis of evolutionary algorithm integration and a fuzzy control model of algorithm parameters. A fuzzy logical controller structure is described in the article. To confirm the method effectiveness a brief program description is reviewed.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Dshalalow, J.H. (ed.): Advances in Queueing Theory, Methods, and Open Problems (Probability and Stochastics Series). CRC Press (1995)
Asmussen, S. (ed): Applied Probability and Queues (Stochastic Modeling and Applied Probability Series Vol. 51). Springer (2010)
Gross, D., Shortle, J.F., Thompson, J.M., Harris, C.M.: Solutions Manual to Accompany Fundamentals of Queueing Theory, 4th edn. Wiley (2008)
Bhat, N.U.: An Introduction to Queueing Theory: Modeling and Analysis in Applications (Statistics for Industry and Technology). Birkhäuser (2008)
Bose, S.K.: An Introduction to Queueing Systems (Network and Systems Management). Kluver Academic/Plenum Publisher, New York (2002)
Ng, C.-H., Boon-Hee, S.: Queueing Modelling Fundamentals: With Applications in Communication Networks, 2nd edn. Wiley (2008)
Gladkov, L.A., Kureychik, V.V., Kureychik, V.M.: Genetic Algorithms. Fizmatlit, Moscow (2010)
Herrera, F., Lozano, M.: Fuzzy adaptive genetic algorithms: design, taxonomy, and future directions. Journal of Soft Computing, pp. 545–562. Springer-Verlag (2003)
Michael, A., Takagi, H.: Dynamic control of genetic algorithms using fuzzy logic techniques. In: Proceedings of the Fifth International Conference on Genetic Algorithms, pp. 76-83. Morgan Kaufmann (1993)
Batyrshin, I.Z., Nedosekin, S.A.: Fuzzy Hybrid Systems. Theory and Practice. Fizmatlit, Moscow (2007)
Gladkov, L., Gladkova, N., Leiba, S.: Manufactoring scheduling problem based on fuzzy genetic algorithm. In: Proceeding of IEEE East-West Design & Test Symposium—(EWDTS’2014), pp. 209–212, Kiev, Ukraine (2014)
Glagkov, L.A., Glagkova, N.V., Leiba, S.N.: Electronic computing equipment schemes elements placement based on hybrid intelligence approach. In: Proceedings of the 4th Computer Science On-line Conference 2015 (CSOC2015), Vol. 2: Software Engineering in Intelligent Systems, № 348, pp. 35–45
Acknowledgment
This research is supported by grants of the Russian science foundation (project № 14-11-00242) in Southern Federal University.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Gladkov, L.A., Gladkova, N.V., Leiba, S.N. (2016). Hybrid Intelligent Approach to Solving the Problem of Service Data Queues. In: Abraham, A., Kovalev, S., Tarassov, V., Snášel, V. (eds) Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16). Advances in Intelligent Systems and Computing, vol 450. Springer, Cham. https://doi.org/10.1007/978-3-319-33609-1_38
Download citation
DOI: https://doi.org/10.1007/978-3-319-33609-1_38
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-33608-4
Online ISBN: 978-3-319-33609-1
eBook Packages: EngineeringEngineering (R0)