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On the optimal control of loss probability and profit in a GI/C-BMSP/1/N queueing system

Author

Listed:
  • Abhijit Datta Banik

    (Indian Institute of Technology Bhubaneswar)

  • Souvik Ghosh

    (Amity University)

  • M. L. Chaudhry

    (Royal Military College of Canada)

Abstract

This paper deals with a single server queueing system where the waiting space is limited. The server serves the customer in batches. The arrival process is considered to be renewal type and the services are considered to be correlated which has been presented by a continuous-time batch Markovian service process (C-BMSP). Distribution of the system length at pre-arrival instant of a customer and at an arbitrary-epoch have been determined for this queueing system. These probability distributions have been used for obtaining the blocking probability of an arbitrary customer, expected system-length, expected waiting time of an arbitrary customer in the system, and several other important performance measures. This model may find application in queueing systems involving inventory where delay in demand may lead to perishing of goods due to long wait in the system. Also, a profit function has been derived for such a queueing model to maximize the profit from the system for certain model parameters. Finally, assuming that the inter-arrival time follows phase-type distribution, a few numerical examples have been presented in the form of graphs and tables.

Suggested Citation

  • Abhijit Datta Banik & Souvik Ghosh & M. L. Chaudhry, 2020. "On the optimal control of loss probability and profit in a GI/C-BMSP/1/N queueing system," OPSEARCH, Springer;Operational Research Society of India, vol. 57(1), pages 144-162, March.
    • Handle: RePEc:spr:opsear:v:57:y:2020:i:1:d:10.1007_s12597-019-00409-9
    DOI: 10.1007/s12597-019-00409-9
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    References listed on IDEAS

    as
    1. Souvik Ghosh & A. D. Banik, 2018. "Computing conditional sojourn time of a randomly chosen tagged customer in a $$\textit{BMAP/MSP/}1$$ BMAP / MSP / 1 queue under random order service discipline," Annals of Operations Research, Springer, vol. 261(1), pages 185-206, February.
    2. A. Banik & U. Gupta, 2007. "Analyzing the finite buffer batch arrival queue under Markovian service process: GI X /MSP/1/N," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(1), pages 146-160, July.
    3. M. L. Chaudhry & A. D. Banik & A. Pacheco, 2017. "A simple analysis of the batch arrival queue with infinite-buffer and Markovian service process using roots method: $$ GI ^{[X]}/C$$ G I [ X ] / C - $$ MSP /1/\infty $$ M S P / 1 / ∞," Annals of Operations Research, Springer, vol. 252(1), pages 135-173, May.
    4. Bar-Lev, Shaul K. & Parlar, Mahmut & Perry, David & Stadje, Wolfgang & Van der Duyn Schouten, Frank A., 2007. "Applications of bulk queues to group testing models with incomplete identification," European Journal of Operational Research, Elsevier, vol. 183(1), pages 226-237, November.
    5. Bar-Lev, S.K. & Parlar, M. & Perry, D. & Stadje, W. & van der Duyn Schouten, F.A., 2007. "Applications of bulk queues to group testing models with incomplete identification," Other publications TiSEM 0b1bfa5e-c1e6-43ec-9684-1, Tilburg University, School of Economics and Management.
    6. Winfried K. Grassmann & Michael I. Taksar & Daniel P. Heyman, 1985. "Regenerative Analysis and Steady State Distributions for Markov Chains," Operations Research, INFORMS, vol. 33(5), pages 1107-1116, October.
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