家庭护理人员协同调度与路径规划研究

Collaborative routing and scheduling problem of home health care

随着我国老龄人口数量的不断增长以及家庭护理观念的普及,用户日渐青睐居家接受个性化的家庭护理服务。然而护理服务资源在不同区域、机构的配置程度存在差异,单一机构难以满足用户快速增长的多样化、个性化需求。为缓解护理服务资源供需不均衡情况,将协同服务思想引入家庭护理,提出家庭护理人员协同调度与路径规划问题,考虑多个护理中心协同服务同一客户的不同需求。在现有护理资源不变的条件下,通过对资源统筹优化,提高护理资源利用率,使得护理人员的调度方案更加灵活合理,在满足客户需求的前提下达到降低护理中心运营成本的目的。为了研究该问题,首先建立了以护理人员启用、行驶、正常工作、加班工作总成本最小,包含客户需求、护理人员工作时长等约束的家庭护理人员协同调度的数学规划模型;其次,考虑护理人员和客户需求所具备的特性,根据贪心、随机、自适应思想,结合贪心随机启发式和迭代局部搜索等多种方法设计了具有自适应反馈机制的混合贪心随机自适应搜索算法;最后,基于标准算例的仿真实验测试评估所设计算法的性能。实验结果表明:设计的算法相比优化软件GUROBI和标准GRASP能够更加高效、高质量地求解家庭护理人员协同调度与路径规划问题;同时引入协同思想能够大幅缩减运营成本并提高护理人员利用率。

Traditional outpatient medical services require patients to visit hospitals for treatment,inhibiting patients from receiving convenient,efficient,and high-quality medical services.With the popularization and application of internet technology,the emergence of“internet-nursing service”has enabled users to receive health care at home,bringing them great convenience and efficiency.However,the supply of medical resources varies across different regions and institutions,and it is difficult for a single institution to meet the diverse and personalized needs of users with rapid growth.Collaborative services were introduced into home health care as a solution to the imbalanced supply and demand for medical resources,and the collaborative multi-depot home health care problem was discussed,considering the collaborative service of multiple care centers for multi-demand customers.This study aims to minimize the operating costs of care centers by coordinating and optimizing medical resources and by planning flexible and reasonable scheduling plans for caregivers while meeting customers’needs.The problem is formulated as a mathematical programming model with the objective of minimizing the total cost of fixed,traveling,normal working,overtime working,and constraints of customer demand and caregiver working duration.Moreover,considering the characteristics of the studied problem,a hybrid greedy randomized adaptive search procedure with an adaptive feedback mechanism combining greedy random heuristic and iterative local search methods was designed based on greedy,random,and adaptive ideas.Finally,the performance of the designed algorithm was evaluated by testing benchmark instances in simulation experiments.Compared with the optimization software GUROBI and the standard greedy randomized adaptive search procedure,the proposed algorithm solved the studied problem more efficiently,providing high-quality solutions.Therefore,collaborative services can significantly reduce operating costs and improve caregiver utilization.