Abstract: In order to solve the seat-occupying and seat arrangement problems in libraries, this paper works onevaluating and improving the auto seating arrangement system in libraries. Take a university library for example. A Multi-Objective Grey Wolf Optimizer model (MOGWO) for solving the problem of how to allocate seat resource fairly is built under multi-objective constraints, and the different popularity among seats which is measured by Theil index is listed. Based on the reservation function, this system can reasonably restrict readers' seat selection behaviors. Finally, computational results based on high frequency data are provided to demonstrate the effectiveness of the model and the algorithm. This paper also puts forward some corresponding management suggestions and supports the decision of making management plans.

Key words: seat resource, Theil index, MOGWO, library management, grey target model

摘要： 针对图书馆占座和座位分配问题,评价并改进图书馆的自助选座系统。以某高校图书馆为研究对象,在多目标约束条件下构建了实现座位资源使用均衡化的多目标灰狼算法(MOGWO)优化模型,提出采用泰尔系数衡量不同区域的座位热度差异,并设计自助选座系统的预约功能,从而更加人性化地约束读者的选座行为。采用某高校图书馆的高频记录数据证实了模型及算法的有效性,并提出可操作性建议,为提升图书馆管理效率提供决策参考。

关键词: 座位资源, 泰尔系数, 多目标灰狼算法, 图书馆管理, 灰靶模型