IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v68y2018i3d10.1007_s11235-017-0397-x.html
   My bibliography  Save this article

Optimum alternatives of tandem G/G/K queues with disaster customers and retrial phenomenon: interactive voice response systems

Author

Listed:
  • A. Azadeh

    (University of Tehran)

  • M. S. Naghavi lhoseiny

    (University of Tehran)

  • V. Salehi

    (University of Tehran)

Abstract

In this paper, we study a tandem queue with retrials where the queue experiences disasters. The probability of system failure depends on the strength of equipment, which makes servers idle and causes the removal of all customers in queues and service areas at once. The customers in the queue are forced to orbit in a retrial queue during the system failure where they decide whether or not to come back to the system. Reducing the disaster arrival rate (the probability of system failure) by employing more servers and reducing the number of lost customers is very costly. Moreover, it is important to service the customers with no interruption and reduce the time in system. The developed scenarios are compared in five dimensions including time in system, cost of lost customer, operator cost, the number of uninterrupted service customers and cost of reducing disaster arrival rate (or empowering system cost). The scenarios are modeled by computer simulation. Then, the optimal scenario is chosen using data envelopment analysis. The optimal scenario maximizes system efficiency in terms of disaster arrival rate, cost of lost customers and the number of satisfied customers. In the main problem, the disasters arrive at the system according to Poisson process; the effect of changing the distribution function of disaster arrival has been investigated finally. We are among the first ones to study and optimize G/G/K tandem queuing systems with system failures and retrial phenomena in interactive voice response systems.

Suggested Citation

  • A. Azadeh & M. S. Naghavi lhoseiny & V. Salehi, 2018. "Optimum alternatives of tandem G/G/K queues with disaster customers and retrial phenomenon: interactive voice response systems," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 68(3), pages 535-562, July.
    • Handle: RePEc:spr:telsys:v:68:y:2018:i:3:d:10.1007_s11235-017-0397-x
    DOI: 10.1007/s11235-017-0397-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-017-0397-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11235-017-0397-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, September.
    2. Artalejo, Jesus R. & Economou, Antonis & Gómez-Corral, Antonio, 2008. "Algorithmic analysis of the Geo/Geo/c retrial queue," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1042-1056, September.
    3. Raj Srinivasan & Jérome Talim & Jinting Wang, 2004. "Performance analysis of a call center with interactive voice response units," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(1), pages 91-110, June.
    4. Wang, Jinting & Liu, Bin & Li, Jianghua, 2008. "Transient analysis of an M/G/1 retrial queue subject to disasters and server failures," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1118-1132, September.
    5. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    6. William W. Cooper & Lawrence M. Seiford & Joe Zhu, 2011. "Data Envelopment Analysis: History, Models, and Interpretations," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 1-39, Springer.
    7. Levitin, Gregory & Amari, Suprasad V., 2008. "Multi-state systems with multi-fault coverage," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1730-1739.
    8. Haughton, Michael & Sapna Isotupa, K.P., 2012. "Scheduling commercial vehicle queues at a Canada–US border crossing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 190-201.
    9. John D. C. Little, 1961. "A Proof for the Queuing Formula: L = (lambda) W," Operations Research, INFORMS, vol. 9(3), pages 383-387, June.
    10. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    11. Alnowibet, Khalid Abdulaziz & Perros, Harry, 2009. "Nonstationary analysis of the loss queue and of queueing networks of loss queues," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1015-1030, August.
    12. Elena Beccalli & Barbara Casu & Claudia Girardone, 2006. "Efficiency and Stock Performance in European Banking," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(1‐2), pages 245-262, January.
    13. Azadeh, A. & Moghaddam, M. & Asadzadeh, S.M. & Negahban, A., 2011. "An integrated fuzzy simulation-fuzzy data envelopment analysis algorithm for job-shop layout optimization: The case of injection process with ambiguous data," European Journal of Operational Research, Elsevier, vol. 214(3), pages 768-779, November.
    14. Azadeh, A. & Faiz, Z.S. & Asadzadeh, S.M. & Tavakkoli-Moghaddam, R., 2011. "An integrated artificial neural network-computer simulation for optimization of complex tandem queue systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(4), pages 666-678.
    15. Azadeh, A. & Ghaderi, S.F. & Nasrollahi, M.R., 2011. "Location optimization of wind plants in Iran by an integrated hierarchical Data Envelopment Analysis," Renewable Energy, Elsevier, vol. 36(5), pages 1621-1631.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Carlos Chaves & Abhijit Gosavi, 2022. "On general multi-server queues with non-poisson arrivals and medium traffic: a new approximation and a COVID-19 ventilator case study," Operational Research, Springer, vol. 22(5), pages 5205-5229, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Matthias Klumpp & Dominic Loske, 2021. "Sustainability and Resilience Revisited: Impact of Information Technology Disruptions on Empirical Retail Logistics Efficiency," Sustainability, MDPI, vol. 13(10), pages 1-20, May.
    2. Duk Hee Lee & Il Won Seo & Ho Chull Choe & Hee Dae Kim, 2012. "Collaboration network patterns and research performance: the case of Korean public research institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 925-942, June.
    3. Feng Li & Qingyuan Zhu & Jun Zhuang, 2018. "Analysis of fire protection efficiency in the United States: a two-stage DEA-based approach," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 23-68, January.
    4. Margareta Gardijan & Zrinka Lukač, 2018. "Measuring the relative efficiency of the food and drink industry in the chosen EU countries using the data envelopment analysis with missing data," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(3), pages 695-713, September.
    5. Imanirad, Raha & Cook, Wade D. & Aviles-Sacoto, Sonia Valeria & Zhu, Joe, 2015. "Partial input to output impacts in DEA: The case of DMU-specific impacts," European Journal of Operational Research, Elsevier, vol. 244(3), pages 837-844.
    6. Feng Li & Qingyuan Zhu & Liang Liang, 2019. "A new data envelopment analysis based approach for fixed cost allocation," Annals of Operations Research, Springer, vol. 274(1), pages 347-372, March.
    7. Petridis, Konstantinos & Malesios, Chrisovalantis & Arabatzis, Garyfallos & Thanassoulis, Emmanuel, 2013. "Efficiency analysis of forestry journals: Suggestions for improving journals’ quality," Journal of Informetrics, Elsevier, vol. 7(2), pages 505-521.
    8. Shaher Z Zahran & Jobair Bin Alam & Abdulrahem H Al-Zahrani & Yiannis Smirlis & Stratos Papadimitriou & Vangelis Tsioumas, 2017. "Analysis of port authority efficiency using data envelopment analysis," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(3), pages 518-537, August.
    9. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    10. Aziz KUTLAR & Ali KABASAKAL & Adem BABACAN, 2015. "Dynamic Efficiency of Turkish Banks: a DEA Window and Malmquist Index Analysis for the Period of 2003-2012," Sosyoekonomi Journal, Sosyoekonomi Society, issue 23(24).
    11. Muhammad Nisar Khan & Adnan Ahmad & Noor Jehan, 2018. "Pakistani Firms' Efficiency: An Empirical Study of Pakistan Stock Exchange through Data Envelopment Analysis," Global Social Sciences Review, Humanity Only, vol. 3(3), pages 158-174, September.
    12. Jaime Bonet-Morón & Jhorland Ayala-García, 2016. "La brecha fiscal territorial en Colombia," Documentos de trabajo sobre Economía Regional y Urbana 235, Banco de la Republica de Colombia.
    13. Amir Moradi-Motlagh & Ali Salman Saleh, 2014. "Re-Examining the Technical Efficiency of Australian Banks: A Bootstrap DEA Approach," Australian Economic Papers, Wiley Blackwell, vol. 53(1-2), pages 112-128, June.
    14. Yang Li & An-Chi Liu & Shu-Mei Wang & Yiting Zhan & Jingran Chen & Hsiao-Fen Hsiao, 2022. "A Study of Total-Factor Energy Efficiency for Regional Sustainable Development in China: An Application of Bootstrapped DEA and Clustering Approach," Energies, MDPI, vol. 15(9), pages 1-13, April.
    15. Lim, Sungmook & Zhu, Joe, 2013. "Incorporating performance measures with target levels in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 230(3), pages 634-642.
    16. Jaime Bonet‐Morón & Jhorland Ayala‐García, 2020. "The territorial fiscal gap in Colombia," Regional Science Policy & Practice, Wiley Blackwell, vol. 12(1), pages 7-24, February.
    17. Aytekin, Ahmet & Ecer, Fatih & Korucuk, Selçuk & Karamaşa, Çağlar, 2022. "Global innovation efficiency assessment of EU member and candidate countries via DEA-EATWIOS multi-criteria methodology," Technology in Society, Elsevier, vol. 68(C).
    18. Fazlollahi, Ariyan & Franke, Ulrik, 2018. "Measuring the impact of enterprise integration on firm performance using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 200(C), pages 119-129.
    19. Haidar Haidar, 2022. "Efficiency of Syrian Banks: A Nonparametric Frontier Approach," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-2.
    20. Javad Vakili & Hanieh Amirmoshiri & Rashed Khanjani Shiraz & Hirofumi Fukuyama, 2020. "A modified distance friction minimization approach in data envelopment analysis," Annals of Operations Research, Springer, vol. 288(2), pages 789-804, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:telsys:v:68:y:2018:i:3:d:10.1007_s11235-017-0397-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.