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A finite-source inventory system with postponed demands and modified M vacation policy

Author

Listed:
  • I. Padmavathi

    (Madurai Kamaraj University)

  • A. Shophia Lawrence

    (Madurai Kamaraj University)

  • B. Sivakumar

    (Madurai Kamaraj University)

Abstract

We study a finite source (s, S) inventory system with postponed demands and server vacation. We adopt a modified M vacation policy which is defined as: Whenever the inventory level reaches zero, the server goes to inactive period which comprises the inactive-idle and vacation period. If replenishment occurs during the inactive-idle period, the server becomes active immediately, or otherwise he goes for a vacation period. The server can take at most M inactive periods repeatedly until replenishment takes place. This inactive-idle time, the vacation time and lead time follow independent PH distributions. After the M t h inactive period, the server remains dormant in the system irrespective of the replenishment of order. Demands that occur during stock out or inactive periods, enter the pool and these demands are selected if the inventory level is above s. The inter-selection time follows exponential distribution. The joint distribution of the mode of the server, server status, the inventory level and the number of demands in the pool is obtained in the steady state. We have derived several system performance measures and total expected cost function. The results are illustrated numerically.

Suggested Citation

  • I. Padmavathi & A. Shophia Lawrence & B. Sivakumar, 2016. "A finite-source inventory system with postponed demands and modified M vacation policy," OPSEARCH, Springer;Operational Research Society of India, vol. 53(1), pages 41-62, March.
    • Handle: RePEc:spr:opsear:v:53:y:2016:i:1:d:10.1007_s12597-015-0224-7
    DOI: 10.1007/s12597-015-0224-7
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    References listed on IDEAS

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    1. T. Deepak & V. Joshua & A. Krishnamoorthy, 2004. "Queues with postponed work," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 12(2), pages 375-398, December.
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    Cited by:

    1. N. Saranya & A. Shophia Lawrence, 2019. "A stochastic inventory system with replacement of perishable items," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 563-582, June.
    2. Yuying Zhang & Dequan Yue & Wuyi Yue, 2022. "A queueing-inventory system with random order size policy and server vacations," Annals of Operations Research, Springer, vol. 310(2), pages 595-620, March.

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