Home Health Care Supply Chain (HHCSC) is an interesting and widespread topic in developed countries due to an aging population's care. Home care services aim to provide general hygiene care and nursing considering dependency for older people. One of the real circumstances in such systems is that the two parties, caregivers and patients, adopt their decisions at different decision levels. From the perspective of HHCSC companies, the position of pharmacies, scheduling and routing of nurses, and the quantity of releasing drugs have been important and open issues. Another real supposition in HHCSC networks is that the patients choose their company and its services according to its cost. Contrary to previous works, here, we firstly consider outsourcing for patients’ demand to receive direct services from a hospital as a real assumption. Besides, this work develops a bi-level programming model as a static Stackelberg game between nurses and patients within the framework of HHCSC. Another novelty of this work is to utilize capable meta-heuristics reported in the literature as well as hybrid ones. To validate the application of meta-heuristics in small sizes, a solution procedure combining a heuristic and exact method is utilized. Finally, comparative analysis of the algorithm, probing the model using a real-case study, and some sensitivity analyses are done.

由于人口老龄化，家庭医疗保健供应链 (HHCSC) 在发达国家是一个有趣且广泛的话题。家庭护理服务旨在为老年人提供考虑到依赖性的一般卫生保健和护理。这种系统中的真实情况之一是护理人员和患者两方在不同的决策级别采用他们的决定。从 HHCSC 公司的角度来看，药房的位置、护士的调度和路线以及释放药物的数量一直是重要和公开的问题。HHCSC 网络中的另一个真实假设是患者根据成本选择他们的公司及其服务。与之前的工作相反，在这里，我们首先考虑将患者从医院直接获得服务的需求外包作为一个真实的假设。除了，这项工作开发了一个双层编程模型，作为 HHCSC 框架内护士和患者之间的静态 Stackelberg 博弈。这项工作的另一个新颖之处是利用文献中报道的有能力的元启发式以及混合式元启发式方法。为了验证元启发式在小尺寸中的应用，使用了结合启发式和精确方法的求解过程。最后，对算法进行了比较分析，使用实际案例研究对模型进行了探索，并进行了一些敏感性分析。使用结合启发式和精确方法的求解过程。最后，对算法进行了比较分析，使用实际案例研究对模型进行了探索，并进行了一些敏感性分析。使用结合启发式和精确方法的求解过程。最后，对算法进行了比较分析，使用实际案例研究对模型进行了探索，并进行了一些敏感性分析。