4 edition of Dynamic scheduling of a multiclass make-to-stock queue found in the catalog.
by Sloan School of Management, Massachusetts Institute of Technology in Cambridge, Mass
Written in English
|Other titles||Multiclass make-to-stock queue, Dynamic scheduling of a.|
|Statement||Lawrence M. Wein.|
|Series||Working paper -- No. 3113-90-MSA, Working paper (Sloan School of Management) -- 3113-90.|
|Contributions||Sloan School of Management.|
|The Physical Object|
|Pagination||38 p. :|
|Number of Pages||38|
The concept of priority indices defined to discuss the Restless Bandit Problem (RBP) furnish a relevant approximative framework to approach the optimal scheduling of a multi-products make-to-stock production when no setup cost and/or time are incurred. The resulting policy involves switching curves and hedging stocks. At each time, the index policy selects the item to be produced for any Author: F. Dusonchet, M.-O. Hongler. Restless bandit dynamic allocation indices I: Single-project case and optimal control of a make-to-stock M/G/1 queue. (). Restless bandit marginal productivity indices, diminishing returns, and scheduling a multiclass make-to-order/-stock : José Niño-Mora.
Buy lawrence m wein Books at Shop amongst our popular books, includ Dynamic Scheduling of a Multiclass Make-to-Stock Queue (Classic Reprint), Dynamic Scheduling of a Multiclass Make-to-Stock Queue (Classic Reprint) and more from lawrence m wein. Free shipping and pickup in store on eligible orders. scheduling have developed independently for many years and, as a consequence, have dif-ferent performance measures of interest, standard problem settings, and assumptions. In this paper, we take steps toward the integration of queueing and scheduling by studying two dynamic scheduling problems and making the following contributions:File Size: KB.
Restless bandit dynamic allocation indices II: Multi-project case and dynamic scheduling of a multiclass maketo-order/-stock M/G/1 queue J. Niño-Mora Working Paper The First Comprehensive Book on the Subject Focusing on the underlying structure of a system, Optimal Design of Queueing Systems explores how to set the parameters of a queueing system, such as arrival and service rates, before putting it into operation. It considers various objectives, comparing individually optimal (Nash equilibrium), socially optimal, class optimal, and facility optimal.
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Motivated by make-to-stock production systems, we consider a scheduling problem for a single server queue that can process a variety of different job classes. After jobs are processed, they enter a finished goods inventory that services customer by: workingpaper choolofmanagement dynamicschedulingofamulticlass make-to-stockqueue sloanschoolofmanagment,mit workingpapernomsa massachusetts instituteoftechnology 50memorialdrive cambridge,massachusetts of jobs in a conventional multiclass queue has been examined thoroughly (see, for example, Klimov ), there are no studies that explicitly analyze the problem of scheduling a multiclass make-to-stock queue.
Graves (), and Bemelmans and Wijngaard () consider aggregation approaches to scheduling single machine, multiproduct production. texts All Books All Texts latest This Just In Smithsonian Libraries FEDLINK Dynamic scheduling of a multiclass make-to-stock queue Item Preview remove-circle Dynamic scheduling of a multiclass make-to-stock queue by Wein, Lawrence M; Sloan School of Management.
Publication date Pages: and a backorder cost for each request on backorder (per unit of time). The make-to-stock manufacturing system is modeled as a multi-class single-server queueing system. The system manager seeks to maximize the long-run average proﬁt by making dynamic pricing, outsourcing, and scheduling decisions: First, she.
Dynamic Scheduling of a Multiclass Queue in the Halﬁn–Whitt Heavy Traﬃc Regime The paper is concerned with dynamic control of a multi-class Markovian service system in which one pool of servers attends to several customer classes.
A schematic description is given in Figure 1. Key words: multiclass queue, abandonment, uid model, dynamic scheduling, knapsack problem 1. Introduction Inthe number of left-without-being-seen (LWBS) patients in the United States was million (The National Hospital Ambulatory Medical Care Survey, NHAMCS) for the most common reason of being \fed up with waiting" (Rowe et al.
()). and longest queue policies, no performance guarantees are available and both have obvious deﬂciencies in the structure of the control. This paper develops and tests several new scheduling policies. The system con-sidered is a multiclass M=M=1 make-to-stock queue.
Preemptive resume scheduling is allowed and there are no set-up costs or times Cited by: Dynamic Scheduling of Multiclass Queueing Networks Approved: Prof. Jiangang Dai, Chairman Prof.
Leon McGinnis Prof. Richard Serfozo Prof. John Vande Vate. The resulting index policy has been derived and tested computationally in , for scheduling a multiclass MTO M/M/1 queue with convex backorder costs, and in , for scheduling a multiclass MTSB.
A.V. Iyer and A. Jain, The logistics impact of a mixture of order-streams in a manufacturer–retailer system, Manage Sci 49 (), – 19Apurva Jain: Scheduling in a Make-to-Stock Queue Author: Apurva Jain. ing applications, concerning the dynamic scheduling of a multi-productcombined make-to-order (MTO)/make-to-stock (MTS)production-inventory facility, modeled by a multiclass MTO/MTS M/G/1 queue with convex backorder/stock holding cost rates.
Results include a hedging point and index scheduling policy coming. Dynamic scheduling of a multiclass make-to-stock queue By Lawrence M. Wein Publisher: Cambridge, Mass.: Sloan School of Management, Massachusetts Institute of TechnologyAuthor: Lawrence M. Wein. paradigm to study the ED dynamics would be a multiclass many-server queueing system with abandonment (the LWBS phenomenon) as shown in Figure 1.
One of our main results is to introduce a dynamic scheduling policy, which we refer to as the generalized c =h rule (Gc =h), to minimize the long-run average queueing costs and abandon penalties.
We consider a multiclass queueing system with abandonments and general delay costs. A system manager makes dynamic scheduling decisions to minimize long-run average delay and abandonment costs. We consider the three types of delay cost: (i) linear, (ii) convex, and (iii) convex–concave, where the last one corresponds to settings where customers may have a particular Cited by: reported for the Brownian and longest queue policies, no performance guarantees are available and both have obvious deficiencies in the structure of the control.
This paper develops and tests several new scheduling policies. The system con-sidered is a multiclass M/M/1 make-to-stock queue. Preemptive resume scheduling is allowed and no set-up. In this work, the dynamic scheduling of a speciﬁc multiclass stochastic ﬂuid model is studied ﬁrst.
Then, a bridge between the scheduling of stochastic ﬂuid models and that of the queueing networks in a changing environment is established. In the multiclass stochastic ﬂuid model, the focus is on a system with two ﬂuid classes.
Dynamic pricing and scheduling in a multi-class Keywords Dynamic control of queues Multi-class system Dynamic pricing sults are also obtained for the make-to-stock queue model of a production/inventory system in Li , Gayon et al.
. Remark 3 Multi-Class Queue with Deadlines. In the case c k = 0, k = 1,K, the model becomes a multi-class queue with deadlines: customers need to be served before a deadline that is exponentially distributed with parameter θ k and in the case they do not receive service before their deadline they abandon the queue giving a cost d by: Downloadable.
This paper considers the dynamic scheduling problem of a single-server, make-to-stock queue with two products. For the case of Poisson demands and exponential production times, we show that it is optimal to produce the product with the larger b μ index when it is backordered. If the production times are identically distributed, the optimal policy can further be characterized by Cited by:.
The characterization is simple enough to lead to easily implementable heuristics and provides a formal justification of some of the earlier heuristics proposed. 1 Introduction A challenging problem in production control is the dynamic allocation of limited production capacity between different products in a make-to-stock environment.Downloadable (with restrictions)!
Abstract We consider joint capacity–inventory management for multi-server make-to-stock queues operating under a base stock policy. The number of servers corresponds to the capacity decision, and the base stock level is the inventory decision.
Our goal is to minimize a combination of capacity, inventory, and backordering costs. Dynamic Scheduling of a Multi-Class Queue: Discount Optimality (), Operations Research, Vol. 23,  A Diffusion Approximation for the Ruin Function of a Risk Process withFile Size: KB.