同步服务下考虑护工午休的双目标家庭护理人员调度问题

A Bi-objective Home Care Worker Scheduling Problem Considering Lunch Break of Caregivers under Synchronized Service

在家庭护理过程中,行动不便的患者往往需要两名护工同时为他们提供服务,这极大地增加了问题的难度。为实现家庭护理企业降本增效,以及为管理者实际排班提供参考,针对患者的同步服务需求,考虑护工的午休时间,以最小化运营成本和护工不满意度为目标构建了模型。从降级服务和同步服务时间差两方面构建护工不满意度表达式,设计虚拟午休节点处理午休约束。提出了改进的自适应大邻域搜索算法进行求解,该算法与多向局部搜索框架相结合,采用多种启发式初始解策略,设计同步服务判断矩阵,对解的可行性进行验证,针对两个目标分别设计局部搜索算子进一步提升解的质量。采用田口方法对算法参数进行调整并使用超体积指标和空间性分布指标评价解集。对比其他三种多目标启发式方法,所提算法在绝大多数算例上都获得更优的评价指标值,验证了所提算法在该问题上的适用性和优越性。

In the process of home health care,patients with limited mobility often need two caregivers to serve them at the same time,which greatly increases the difficulty of the problem.In order to realize the cost reduction and efficiency increase of home health care enterprises and provide reference for managers'actual scheduling,a model was established.This model focused on the synchronized service demand of patients and considered the lunch break time of caregivers,with the aim of minimizing both operating costs and caregiver dissatisfaction.The expression of caregivers'dissatisfaction considered two aspects:degraded service and synchronized service time difference.To deal with the lunch break constraint,a virtual lunch break node was proposed.An improved adaptive large neighborhood search algorithm was proposed to solve the problem.The algorithm was combined with the multi-directional local search framework.A variety of heuristic initial solution strategies were adopted and the feasibility of the solution was verified by the synchronous service judgment matrix.Further,local search operators were devised for the two objectives to improve the quality of the solution.The Taguchi method was employed to adjust algorithm parameters and the solution set was evaluated using the hyper volume index and spacing metric index.Compared with three other multi-objective heuristic methods,the proposed algorithm achieved better evaluation index values in most examples.This validates the effectiveness and applicability of our algorithm in solving the home health care scheduling problem.