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Optimal appointment scheduling in continuous time: The lag order approximation method

机译:连续时间的最佳约会调度:滞后阶近似方法

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摘要

The service provider is able to schedule arriving clients with the help of an appointment schedule so that the client can arrive for receiving the service at the scheduled time. This can be considered as a two stage problem. In the first stage, the provider schedules the appointments and in the second stage, the server executes the service. The clients present themselves in the random order and request for including them in the schedule. This article discusses the scheduling problem of the service provider in the first stage. A new approximation method of clients service-time distribution is developed that provides a good approximation. In this case a finite number of clients are scheduled before the starting of the service. The service time distribution, and clients loss function due to waiting time, as well as the servers lateness (overtime) are supposed to be known then the objective is to minimize the sum of service idle time, and lateness, and the clients waiting time. Since the exact solution to the problem is computationally difficult, the lag order approximation (the number of predecessors taken in to account) method is proposed that provides reasonably good solutions to the problem. (25 refs.)
机译:服务提供商可以借助约会计划表来计划到达的客户,以便客户可以在计划的时间到达接收服务。这可以认为是两个阶段的问题。在第一阶段,提供者安排约会,在第二阶段,服务器执行服务。客户以随机顺序展示自己,并要求将其包括在时间表中。本文讨论了服务提供商在第一阶段的调度问题。开发了一种新的客户服务时间分配的近似方法,该方法可以提供良好的近似。在这种情况下,将在服务启动之前安排有限数量的客户端。应该知道服务时间分配以及由于等待时间导致的客户端丢失功能以及服务器延迟(超时),然后目标是使服务空闲时间,延迟和客户端等待时间的总和最小化。由于对问题的精确解决方案在计算上很困难,因此提出了滞后阶近似(考虑到前任者的数量)方法,为问题提供了合理的解决方案。 (25篇)

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  • 来源
    《Operations Research》 |2016年第3期|231-232|共2页
  • 作者单位

    McKinsey & Company, Amstel 344,1017 AS Amsterdam, The Netherlands;

    Institute of business and Industrial Statistics, University of Amsterdam,Plantage Muidergracht 12,1018 TV Amsterdam,The Netherlands;

    Institute of business and Industrial Statistics, University of Amsterdam,Plantage Muidergracht 12,1018 TV Amsterdam, The Netherlands,and EY Transaction Advisory Services, Antonio Vivaldistraat 150,1083 HP Amsterdam, The Netherlands;

    Stochastic Operations Research, Department of Mathematics,VU University Amsterdam, De Boelelaan 1081 a,1081HV Amsterdam, The Netherlands;

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