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Demand-driven scheduling of movies in a multiplex

机译:需求驱动的多路电影调度

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This paper is about a marketing decision support system in the movie industry. The decision support system of interest is a model that generates weekly movie schedules in a multiplex movie theater. A movie schedule specifies, for each day of the week, on which screen(s) different movies will be played, and at which time(s). The model integrates elements from marketing (the generation of demand figures) with approaches from operations research (the optimization procedure). Therefore, it consists of two parts: (i) conditional forecasts of the number of visitors per show for any possible starting time, and (ii) a scheduling procedure that quickly finds a near optimal schedule (which can be demonstrated to be close to the optimal schedule). To generate this schedule, we formulate the "movie scheduling problem" as a generalized set partitioning problem. The latter is solved with an algorithm based on column generation techniques. We tested the combined demand forecasting/schedule optimization procedure in a multiplex in Amsterdam, generating movie schedules for fourteen weeks. The proposed model not only makes movie scheduling easier and less time consuming, but also generates schedules that attract more visitors than current "intuition-based" schedules.
机译:本文是关于电影行业的营销决策支持系统的。感兴趣的决策支持系统是一种模型,该模型在多路电影院中生成每周电影时间表。电影时间表为一周中的每一天指定了将在哪个屏幕上播放不同的电影以及在哪个时间播放。该模型将营销(需求数据的生成)中的要素与运筹学(优化程序)中的方法相结合。因此,它由两部分组成:(i)在任何可能的开始时间对每个节目的访问者数量进行有条件的预测,以及(ii)快速找到接近最佳时间表的安排程序(可以证明该时间表接近于最佳时间表)。最佳时间表)。为了生成此时间表,我们将“电影时间表问题”公式化为广义集合划分问题。后者通过基于列生成技术的算法解决。我们在阿姆斯特丹的一个电影院中测试了组合的需求预测/时间表优化程序,生成了十四周的电影时间表。所提出的模型不仅使电影排程更容易且耗时更少,而且所产生的排程比当前的“基于直觉的”排程吸引了更多的观众。

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