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首页> 外文期刊>IEEE transactions on automation science and engineering >Optimizing Hospital Emergency Department Layout via Multiobjective Tabu Search
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Optimizing Hospital Emergency Department Layout via Multiobjective Tabu Search

机译:通过多目标禁忌搜索优化医院急诊科布局

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Hospital department layout problems (HDLPs) are significant in enhancing service quality and reducing patients' travel distance and time. Their studies are scarce in comparison with those for facility layout problems in manufacturing systems. Existing approaches to HDLPs usually adopt simplified models and thus gain very limited applications in a real world. HDLPs typically involve multiple objectives that may conflict with each other. There have been no studies on their multiobjective heuristic approaches to our best knowledge. In this paper, we propose multiobjective tabu search (MTS) for a real-world HDLP. Beside the frequently used objective of flow cost, ensuring the closeness among certain departments is introduced as another one. A solution coding scheme is designed to represent a solution. A penalty function is devised to handle infeasible solutions. Local search is integrated into tabu search to optimize the assignment of departments. Experiment results show that MTS is able to produce Pareto solutions that outperform those of the comparative method. Compared to the actually implemented layout, solutions produced by MTS can save about 5%-15% patients' travel time (distance).Note to Practitioners-Layout design of hospital departments is significant in enhancing service quality and reducing patients' travel distance. A real-world department layout problem is difficult to solve since many factors need to be considered and multiple optimization objectives must be sought. This paper presents a multiobjective tabu search approach for such a problem with both objectives to minimize patients' flow cost and departments' closeness. This approach is able to provide multiple Pareto solutions (layouts) for decision makers to choose based on their preferences. Layouts created by this approach can significantly reduce patients' travel time (distance) while satisfying the closeness requirement of departments.
机译:医院部门布局问题(HDLP)对于提高服务质量并减少患者的出行距离和时间很重要。与制造系统中的设施布局问题相比,他们的研究很少。现有的HDLP方法通常采用简化的模型,因此在现实世界中获得的应用非常有限。 HDLP通常涉及可能相互冲突的多个目标。尚未对其最佳目标的多目标启发式方法进行研究。在本文中,我们为现实世界的HDLP提出了多目标禁忌搜索(MTS)。除了经常使用的流量成本目标外,还要确保某些部门之间的紧密联系。解决方案编码方案旨在表示一个解决方案。设计了惩罚函数来处理不可行的解决方案。本地搜索已集成到禁忌搜索中,以优化部门分配。实验结果表明,MTS能够产生优于比较方法的Pareto解决方案。与实际实施的布局相比,MTS生产的解决方案可以节省大约5%-15%的患者出行时间(距离)。执业医生注意-医院部门的布局设计对于提高服务质量和缩短患者的出行距离具有重要意义。现实世界中的部门布局问题难以解决,因为需要考虑许多因素,并且必须寻求多个优化目标。本文针对此类问题提出了一种多目标禁忌搜索方法,其目的是最大程度地减少患者的流动成本和部门之间的亲密关系。这种方法能够为决策者提供基于其偏好的多种Pareto解决方案(布局)。通过这种方法创建的布局可以显着减少患者的旅行时间(距离),同时满足部门的紧密性要求。

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