Optimal control of a production–inventory system with customer impatience

Benjaafar, Saif; Gayon, Jean-Philippe; Tepe, Seda

doi:10.1016/j.orl.2010.03.008

Cited by 60 publications

(38 citation statements)

References 24 publications

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“…[1,2,3,4,5]). Several papers investigate the scheduling of different classes of jobs in a system with abandonment in order to minimize the (weighted) number of late jobs.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal static priority rules for stochastic scheduling with impatience

Salch

Gayon

Lemaire

2013

Operations Research Letters

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We consider a stochastic scheduling problem with impatience to the end of service or impatience to the beginning of service. The impatience of a job can be seen as a stochastic due date. Processing times and due dates are random variables. Jobs are processed on a single machine with the objective to minimize the expected weighted number of tardy jobs in the class of static list scheduling policies. We derive optimal schedules when processing times and due dates follow different probability distributions.

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“…[1,2,3,4,5]). Several papers investigate the scheduling of different classes of jobs in a system with abandonment in order to minimize the (weighted) number of late jobs.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal static priority rules for stochastic scheduling with impatience

Salch

Gayon

Lemaire

2013

Operations Research Letters

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“…They obtained that the model with buffer size equal to the inventoried items is the best profitable model for practical purposes. Benjaafar et al (2010) analyzed a production inventory system as a Markov decision process and compared the performance of the optimal policy against several other policies and obtained that performance is poor for those models that ignore impatience of the customer. Chang and Lu (2011) studied a serial production inventory system by providing a phase-type approximation and obtained good estimates for performance measures such as fill rate and mean queue-length distributions of each station.…”

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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“…Thus, it is assumed that all customers are willing to wait during shipment consolidation, and all orders would be met. However, impatient customers may cancel their orders when delivery time increases [11], and delivery time uncertainty decreases customer satisfaction [12]. There is a trade-off between minimizing the cost of having a customer to wait and the cost of providing service [13].…”

Section: Introductionmentioning

confidence: 99%

Shipment Consolidation Policy under Uncertainty of Customer Order for Sustainable Supply Chain Management

et al. 2017

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Abstract:With increasing concern over the environment, shipment consolidation has become one of a main initiative to reduce CO 2 emissions and transportation cost among the logistics service providers. Increased delivery time caused by shipment consolidation may lead to customer's order cancellation. Thus, order cancellation should be considered as a factor in order uncertainty to determine the optimal shipment consolidation policy. We develop mathematical models for quantity-based and time-based policies and obtain optimality properties for the models. Efficient algorithms using optimal properties are provided to compute the optimal parameters for ordering and shipment decisions. To compare the performances of the quantity-based policy with the time-based policy, extensive numerical experiments are conducted, and the total cost is compared.

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Optimal control of a production–inventory system with customer impatience

Cited by 60 publications

References 24 publications

Optimal static priority rules for stochastic scheduling with impatience

Optimal static priority rules for stochastic scheduling with impatience

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

Shipment Consolidation Policy under Uncertainty of Customer Order for Sustainable Supply Chain Management

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