Numerical analysis of(s, S) inventory systems with repeated attempts

Artalejo, Jesús R.; Krishnamoorthy, A.; Lopez-Herrero, M. J.

doi:10.1007/s10479-006-5294-8

Cited by 61 publications

(23 citation statements)

References 9 publications

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“…Under these conditions, the following ergodic distribution function for the process X t ( ) is found in [8]:…”

Section: Weak Convergence Of the Ergodic Distribution Of The Process mentioning

confidence: 99%

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On the rate of convergence of the asymptotic expansion for the ergodic distribution of a semi-Markov (s, S) inventory model

Aliyev

Khaniyev

2012

Cybern Syst Anal

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“…Under these conditions, the following ergodic distribution function for the process X t ( ) is found in [8]:…”

Section: Weak Convergence Of the Ergodic Distribution Of The Process mentioning

confidence: 99%

“…Numerous works (see, for example, [1][2][3][4][5][6][7][8][9][10][11]) are devoted to this model. The model is investigated with allowance for requirements of inventory theory, queuing theory, reliability theory, actuarial theory, etc.…”

Section: Introductionmentioning

confidence: 99%

On the rate of convergence of the asymptotic expansion for the ergodic distribution of a semi-Markov (s, S) inventory model

Aliyev

Khaniyev

2012

Cybern Syst Anal

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“…Literature review Artalejo et al (2006) introduced retrial of unsatisfied customers in inventory systems with positive lead time. They compared numerically the efficiency of the generalized truncated model with a model based on finite truncation.…”

Section: Introductionmentioning

confidence: 99%

Analysis of two production inventory systems with buffer, retrials and different production rates

Jose

Nair

2017

J Ind Eng Int

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This paper considers the comparison of two s; S ð Þ production inventory systems with retrials of unsatisfied customers. The time for producing and adding each item to the inventory is exponentially distributed with rate b. However, a production rate ab higher than b is used at the beginning of the production. The higher production rate will reduce customers' loss when inventory level approaches zero. The demand from customers is according to a Poisson process. Service times are exponentially distributed. Upon arrival, the customers enter into a buffer of finite capacity. An arriving customer, who finds the buffer full, moves to an orbit. They can retry from there and interretrial times are exponentially distributed. The two models differ in the capacity of the buffer. The aim is to find the minimum value of total cost by varying different parameters and compare the efficiency of the models. The optimum value of a corresponding to minimum total cost is an important evaluation. Matrix analytic method is used to find an algorithmic solution to the problem. We also provide several numerical or graphical illustrations.

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“…Artalejo [1], Falin & Artalejo [7] and Falin & Templeton [8] provide reviews on this queueing system. A numerical illustration of inventory systems with retrial was studied by Artalejo et al [2]. The study of inventory models with server interruptions is a topic that has received considerable attention in the last decade.…”

Section: Introductionmentioning

confidence: 99%

A retrial queueing-inventory system with J-additional options for service and finite source

Yadavalli

Jeganathan

Venkatesan

et al. 2017

ORiON

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A continuous review (s, S) inventory system at a service facility with finite homogeneous sources of demands and retrial is analysed. The lifetime of each item is assumed to be exponential. Before items are delivered to the customers, some basic service on the item must be performed. It is known as a regular or main service. The service may get interrupted according to a Poisson process and it restarts after an exponentially distributed time. If the server is idle at the time of arrival of a customer and the inventory level is positive, then the service begins immediately. After the completion of regular service, a customer may either abandon the system forever or demand for a second service from the same server, which is multi-optional. If any arriving customer finds that the server is busy or inventory level is zero, he/she either enters into the orbit with probability p or balks (does not enter) with probability 1 − p. The stationary distribution of the number of customers in the system, server status and the inventory level is obtained by the matrix method. The Laplace-Stieltjes transform of the waiting time of the tagged customer is derived. Various system performance measures are derived and the total expected cost rate is computed under a suitable cost structure. A numerical illustration is given.

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Numerical analysis of(s, S) inventory systems with repeated attempts

Cited by 61 publications

References 9 publications

On the rate of convergence of the asymptotic expansion for the ergodic distribution of a semi-Markov (s, S) inventory model

On the rate of convergence of the asymptotic expansion for the ergodic distribution of a semi-Markov (s, S) inventory model

Analysis of two production inventory systems with buffer, retrials and different production rates

A retrial queueing-inventory system with J-additional options for service and finite source

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