Capacitated Two-Echelon Inventory Models for Repairable Item Systems

Avsar, Z.M.; Zijm, Willem H.M.

doi:10.1007/978-1-4615-1019-2_1

Cited by 10 publications

(13 citation statements)

References 19 publications

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“…The simplification we apply, is described in Avsar and Zijm [3]. They replace the central facility, with its base stock policy, by a special state dependent server, which works with speed min{V C + n, k C }µ C , whenever there are n > 0 items at the central facility.…”

Section: An Approximation Of the Fillratementioning

confidence: 99%

“…In the following, suppose that the central facility is replaced by the special server as proposed in Avsar and Zijm [3]. For the new system, the fillrates can be calculated as follows.…”

Section: An Approximation Of the Fillratementioning

confidence: 99%

“…For literature on spare parts managenent, we refer to Sherbrooke [24], Muckstadt [21], Avsar and Zijm [3] and Sleptchenko [25]. In these papers the focus is on multi-echelon inventory systems, (in a multi-echelon system, inventory is stored at different locations).…”

Section: Introductionmentioning

confidence: 99%

“…The quality of service will be given by imposing a small probability that a customer has to wait for service. Since it is very difficult to find this probability analytically, we will approximate it by using the method described by Avzar and Zijm in [3]. In Section 3 we propose a local search heuristic for finding a solution.…”

Section: Introductionmentioning

confidence: 99%

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Locating repair shops in a stochastic environment

Ommeren

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Sleptchenko

2006

Computers & Operations Research

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In this paper we consider a repair shop location problem with uncertainties in demand. New local repair shops have to be opened at a number of locations. At these local repair shops, customers arrive with broken, but repairable, items. Customers go to the nearest open repair shop. Since they want to leave as soon as possible, a (small) inventory of working items is kept at the repair shops. A customer immediately receives a working item from stock, provided that the stock is not empty. If a stockout occurs, the customer has to wait for a working item. The broken items are repaired in the shop and then put in stock. Sometimes, however, a broken item cannot be fixed at the local repair shop, and it has to be sent to a central repair shop. At the central repair shop the same policy with inventory and repair is used.The problem that we focus on, is not only finding locations for the local repair shops, but also minimizing the stock levels at the shops, such that the fraction of customers that can leave the local shops without waiting (the so called fill rate), is above a prespecified level. We assume that the central repair shop is already opened, but that the repair capacity still has to be set. The local repair shops can be opened at a number of locations, which may have different repair capacities.The goal is to minimize the total cost, that is the total cost for keeping the local shops operational, for the transport of items and for the inventory. For this minimizing problem, a local search heuristic with respect to the open locations, repair capacities and inventory levels is presented.

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Section: An Approximation Of the Fillratementioning

confidence: 99%

“…In the following, suppose that the central facility is replaced by the special server as proposed in Avsar and Zijm [3]. For the new system, the fillrates can be calculated as follows.…”

Section: An Approximation Of the Fillratementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Locating repair shops in a stochastic environment

Ommeren

Bumb

Sleptchenko

2006

Computers & Operations Research

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“…A possible cause is the lack of appropriate queuing models to analyse such repair shops until recently. The analysis of spare part networks with finite capacity repair shops using simple first come first serve (FCFS) rule is even not straightforward, as is shown in Diaz and Fu (1997), Avsar and Zijm (2000) and Sleptchenko et al (2002a).…”

Section: Literaturementioning

confidence: 99%