Abstract

Home health care (HHC) logistics have become a hot research topic in recent years due to the importance of HHC services for the care of ageing population. The logistics of HHC services as a routing and scheduling problem can be defined as the HHC problem (HHCP) academically including a set of service centers and a large number of patients distributed in a specific geographic environment to provide various HHC services. The main challenge is to provide a valid plan for the caregivers, who include nurses, therapists, and doctors, with regard to different difficulties, such as the time windows of availability for patients, scheduling of the caregivers, working time balancing, the time and cost of the services, routing of the caregivers, and route balancing for their routes. This study establishes a biobjective optimization model that minimizes (i) the total service time and (ii) the total costs of HHC services to meet the aforementioned limitations for the first time. To the best of the authors’ knowledge, this research is the first of its kind to optimize the time and cost of HHC services by considering the route balancing. Since the model of the developed HHCP is complex and classified as NP-hard, efficient metaheuristic algorithms are applied to solve the problem. Another innovation is the development of a new self-adaptive metaheuristic as an improvement to the social engineering optimizer (SEO), so-called ISEO. An extensive analysis is done to show the high performance of ISEO in comparison with itself and two well-known metaheuristics, i.e. FireFly algorithm and Artificial Bee Colony algorithm. Finally, the results confirm the applicability of new suppositions of the model and further development and investigation of the ISEO more broadly.

中文翻译：

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考虑工作时间和路线平衡的双目标家庭保健物流：自适应的社会工程优化器

摘要

由于HHC服务对于照顾人口老龄化的重要性，因此家庭保健（HHC）物流已成为近年来研究的热点。可以将HHC服务的物流作为路由和调度问题定义为HHC问题（HHCP），从理论上讲，它包括一组服务中心和分布在特定地理环境中以提供各种HHC服务的大量患者。主要的挑战是针对护理人员（包括护士，治疗师和医生）提供有效的计划，以应对不同的困难，例如患者可利用的时间窗，护理人员的日程安排，工作时间平衡，时间和服务成本，看护者的路线安排以及他们路线的路线平衡。这项研究建立了一个双目标优化模型，该模型最小化（i）总服务时间和（ii）HHC服务的总成本，以首次满足上述限制。据作者所知，这项研究是通过考虑路由平衡来优化HHC服务的时间和成本的同类研究。由于已开发的HHCP的模型很复杂并且被归类为NP-hard，因此使用有效的元启发式算法来解决该问题。另一个创新是开发了一种新的自适应元启发式方法，以改进所谓的ISEO的社会工程优化器（SEO）。进行了广泛的分析，显示出ISEO与其自身以及两种著名的元启发式算法（即FireFly算法和人工蜂群算法）相比具有较高的性能。最后，