引用本文:季孟忠,项薇,彭俊,等.基于负荷平衡的柔性预约决策[J].控制与决策,2021,36(1):226-233
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基于负荷平衡的柔性预约决策
季孟忠1, 项薇1,2, 彭俊1, 黄益槐1, 张肖建1, 何达3
(1. 宁波大学机械工程与力学学院,浙江宁波315211;2. 宁波大学先进储能技术与装备研究院,浙江宁波315211;3. 宁波市鄞州区妇幼保健医院,浙江宁波315125)
摘要:
针对目前国内医疗机构普遍以步入病人求诊为主且个别时段密集到达的就诊需求特点,引入负荷均衡的思想,提出一种多目标优化的柔性门诊调度决策方法.根据实际负荷分布,合理利用柔性的预约负荷平衡调整各时段的总负荷,基于多种预约率、预约和排队规则形成方案集,在多目标灰靶决策模型下,优化出各应用场景下的最优调度方案.数值实验表明,所提出模型较其他模型能够有效降低等待时间高达77.2%.在实际应用分析中,所提出模型能够提高有效资源利用率66.7%,降低高空闲时间导致的资源敏感度.
关键词:  预约调度  灰靶决策  步入病人  负荷平衡  柔性预约  预约决策
DOI:10.13195/j.kzyjc.2019.1690
分类号:C931
基金项目:国家自然科学基金青年项目(51705263).
Flexible outpatient appointment decision model with loading balance
JI Meng-zhong1,XIANG Wei1,2,PENG Jun1,HUANG Yi-huai1,ZHANG Xiao-jian1,HE Da3
(1. Faculty of Mechanical Engineering and Mechanics,Ningbo University,Ningbo315211,China;2. Institute of Advanced Energy Storage Technology and Equipment,Ningbo University,Ningbo 315211,China;3. Yinzhou District Maternal and Child Health Care Hospital(Ningbo),Ningbo315125,China)
Abstract:
In view of the medical service demand features faced by the present domestic medical institutions, i.e. mostly the walk-ins patient and the patient arrival surge, the idea of load balancing is introduced and a flexible outpatient scheduling method with multi-objective appointment optimization is proposed. According to the distribution of the actual walk-in load, the total load is balanced with flexible appointment load balance model in each period. Several appointment rules, queuing rules and reservation rates combinations are utilized to integrate a large number of decision schemes. The optimal solution under different scenarios is screened out by multi-attribute decision model of grey targets. The experiments show that the average wait time can be released to 77.2% comparing to other models. Application case show that resource use rate be improved by 66.7% than before, and the resource sensitivity is lower by using the proposed model.
Key words:  appointment scheduling  grey target decision model  walk-in patients  load balancing  flexible appointment  appointment decision

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