Optimal Admission Control and Sequencing in a Make-to-Stock/Make-to-Order Production System

Carr, Scott M.; Duenyas, Izak

doi:10.1287/opre.48.5.709.12401

Cited by 151 publications

(97 citation statements)

References 17 publications

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“…In addition, it does not explicitly address service-level constraints, and it does not characterize systems in which service time distributions may vary among customer classes. Carr and Duenyas (2000) study a job admission and sequencing problem for a single-server queue in the inventory/production setting. Their system has two streams of jobs with different service standards.…”

Section: Related Literaturementioning

confidence: 99%

A Call-Routing Problem with Service-Level Constraints

Gans

Zhou

2003

Operations Research

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We consider a queueing system, commonly found in inbound telephone call centers, that processes two types of work. Type-H jobs arrive at rate H , are processed at rate H , and are served first come, first served within class. A service-level constraint of the form E delay or P delay limits the delay in queue that these jobs may face. An infinite backlog of type-L jobs awaits processing at rate L , and there is no service-level constraint on this type of work. A pool of c identical servers processes all jobs, and a system controller must maximize the rate at which type-L jobs are processed, subject to the service-level constraint placed on the type-H work.We formulate the problem as a constrained, average-cost Markov decision process and determine the structure of effective routing policies. When the expected service times of the two classes are the same, these policies are globally optimal, and the computation time required to find the optimal policy is about that required to calculate the normalizing constant for a simple M/M/c system. When the expected service times of the two classes differ, the policies are optimal within the class of priority policies, and the determination of optimal policy parameters can be determined through the solution of a linear program with O(c 3 ) variables and O(c 2 ) constraints.

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Section: Related Literaturementioning

confidence: 99%

A Call-Routing Problem with Service-Level Constraints

Gans

Zhou

2003

Operations Research

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“…Matsui (1982Matsui ( , 1985 uses semi-Markov decision processes to consider several order selection policies for stochastic job shops with the goal of maximizing the long-term average reward. Carr and Duenyas (2000) use a continuous-time Markov decision process to model a combined make-to-stock/make-to-order manufacturing system in order to decide which orders should be accepted and how many make-to-stock products to make. The authors are able to find the structure of optimal control and sequencing policies.…”

Section: Literature Reviewmentioning

confidence: 99%

Revenue management for manufacturing companies

Pekgün

2012

J Revenue Pricing Manag

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“…Following this approach enables rms to only serve valuable orders and reserve capacity for future orders with higher prot margins. Carr and Duenyas (2000) modeled a combined make-to-stock/make-to-order manufacturing system in order to decide which orders should be accepted and how many make-tostock products to make. The rm was contractually obliged to meet demand for the class of MTS products while for MTO, there was an option to accept or reject an order.…”

Section: Order Selectivity Based On Protmentioning

confidence: 99%

An agent-based model to support negotiation-based order acceptance in a multi-plant enterprise

Mobini

Behdani

Lukszo

et al. 2011

2011 IEEE International Conference on Systems, Man, and Cybernetics

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SummaryOrder acceptance (OA) has a large inuence on the performance of an enterprise. On the one hand, always accepting an order when capacity is available may restrict the system to accept more protable orders in the future. On the other hand, rejecting too many orders leads to low capacity utilization and also has repercussions for future customer relations. In addition, accepting too many orders leads to an over-loaded production environment, where lead times increase and orders are delivered late. Most of these aspects of order acceptance decision-making can be handled by having proper negotiations with customers on order terms. However, this is a complex problem primarily because there are dierent actors who have various (conicting) interests, needs and objectives. Accordingly, to provide insight for the decision makers in the rms in order to develop proper strategies for order acceptance, developing appropriate models seems necessary.The objective in this research is to improve the order acceptance performance of a make-to-order multi-plant enterprise (MPE) by incorporating buyer-seller negotiations in its OA procedure with the main research question of How can the buyer-seller negotiation process contribute to the improvement of order acceptance performance in the multi-plant enterprise?For this purpose, we have developed an agent-based model to support order acceptance decisions in a multi-plant enterprise particularly using dierent negotiation settings.The research starts with literature review on order acceptance in general and negotiation in particular. A gap is identied in the OA literature: the major perspectives on the OA procedure rest on the underlying assumption that order terms are already determined which is not always tenable. In reality, order terms are usually specied by negotiation between the buyer and the seller and they are not predetermined. A negotiation-based order acceptance approach is consequently suggested in order to consider the whole activities in a negotiation process with three phases. The proposed process involves the initiation conditions for negotiation (pre-negotiation phase), the main interaction (negotiation phase) and the consequences of negotiation on the future decisions of the involved actors (post-negotiation phase). This negotiation process is a part of more general negotiation framework which is then extended into a negotiation ontology. The ontology introduces the main concepts and their relations in a negotiation problem. Next, the conceptualization of the order negotiation process in OA and the negotiation ontology are used in developing an agent-based model for buyer-seller negotiations in a case of multi-plant enterprise. The general assumptions and settings for model development are taken from a model have been presented by Behdani et al. (2010) for a lube oil multi-plant case study motivated by a real supply chain.In this research, the previous model is extended by incorporating negotiation between the ii enterprise and its customers on order terms. Final...

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Optimal Admission Control and Sequencing in a Make-to-Stock/Make-to-Order Production System

Cited by 151 publications

References 17 publications

A Call-Routing Problem with Service-Level Constraints

A Call-Routing Problem with Service-Level Constraints

Revenue management for manufacturing companies

An agent-based model to support negotiation-based order acceptance in a multi-plant enterprise

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