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A framework for additional server activation

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper assesses the performance of the queuing system with several fixed and additional multitask servers. The additional server serves customers in the case of necessity to avoid congestion and decrease the number of impatient customers. An additional server will be activated whenever the length of queue becomes greater than or equal to user defined size i.e. threshold value. Also, this server will be switched off when the length of queue falls below user defined size, but ongoing service has to be finished.The main issue is to decide when and how long the additional server would work with customers. This paper proposes a methodology to choose the best activation rule for the work of an additional server, based on the performance evaluation of queuing system. The Petri nets (PN) simulation is used to calculate the performance measures. Relative efficiency evaluation of different activation rules is carried out by data envelopment analysis (DEA). The methodology is applied on real-life data collected from a postal office.
Rocznik
Strony
387--397
Opis fizyczny
Bibliogr. 19
Twórcy
autor
  • University of Belgrade, Faculty of Organizational Sciences, Belgrade, Serbia
Bibliografia
  • 1. Andersen, P., & Petersen, N. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, Vol. 39(10), pp. 1261-1264.
  • 2. Artlejo, J.R., Orlovsky, D.S., & Dudin, A.N. (2005). Multi-server retrial model with variable number of active servers. Computers&Industrial Engineering, Vol. 48, pp. 273-288.
  • 3. Bosetti, V., & Buchner, B. (2009). Data envelopment analysis of different climate policy scenarios. Ecological Economics Vol. 68, pp. 1340-1354.
  • 4. Braglia, M., & Petroni, A. (1999). Data envelopment analysis for dispatching rule selection. Production Planning & Control, Vol. 10, No. 5., pp. 454-461.
  • 5. Charnes, A., Cooper, W. W., & Rhodes, E. L. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, Vol. 2(6), pp. 429-444.
  • 6. Cooper, W. W., Seiford, L. M., & Tone, K. (2006). Introduction to data envelopment analysis and its uses with DEA-solver software and references. Springer.
  • 7. Gharbi, N., & Ioualalen, M. (2010). Numerical investigation of finite-source multiserver systems with different vacation policies. Journal of Computational and Applied Mathematics Vol. 234, pp. 625-635.
  • 8. Jain, M., Sharma, G. C., & Shekhar, C. (2005). Processor-shared service systems with queue- dependent processors . Computers & Operations Research Vol. 32, pp. 629-645.
  • 9. Jensen, K., & Kristensen, L. M. (2009). Coloured Petri nets. Modelling and validation of concurrent systems. Springer.
  • 10. Jensen, K., Kristensen, L. M., & Wells, L. (2007). Coloured Petri nets and CPN Tools for modeling and validation of concurrent systems. International Journal on Software Tools for Technology Transfer (STTT), Vol. 9, Numbers 3-4, pp. 213-254.
  • 11. Kaboudan, M. A. (1998). A dynamic-server queuing simulation. Computers Ops Res., Vol. 25(6), 431-439.
  • 12. Lin, H. T. (2010). Personnel selection using analytic network process and fuzzy data envelopment analysis approaches. Computers & Industrial Engineering Vol. 59, pp. 937-944.
  • 13. Podinovski, V. V. (1999). Side effects of absolute weight bounds in DEA models. EJOR Vol. 115, pp. 583-595.
  • 14. Roll, Y., Cook, W. D., & Golany, B. (1991). Controlling factor weights in data envelopment analysis. HE Transactions Vol. 23, pp. 2-9.
  • 15. Shan, Z., Lin, C.,Yang, Y. (2002). A multiserver multiqueue network: modeling and performance analysis. Journal of University of Science and Technology Beijing, pp. 389-395.
  • 16. Shin, Y. W., & Choo, T. S. (2009). M/M/s queue with impatient customers and retrials. Applied Mathematical Modelling Vol. 33, pp. 2596-2606.
  • 17. Srdjevic, B., Medeiros, Y. D., & Porto, R. L. (2005). Data envelopment analysis of reservoir
  • system performance. Computers & Operations Research Vol. 32, pp. 3209-3226.
  • 18. Thompson, R. G., Singleton, F. D., Trail, R. M., & Smith, B. A. (1986). Comparative site evalutaion for locating a high-energy physics lab in Texas. Interfaces Vol.16, pp. 34-49.
  • 19. Zhang, Z. G., & Tian, N. (2004). An analysis of queueing systems with multi-task servers. EJOR Vol. 156, pp. 375-389.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPP2-0020-0063
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