Optimal multiresource planning for the elderly care system: a case study

This paper investigates an optimal long-term bed and caregiver plan for the elderly care system (ECS) to meet the increasing care demand due to accelerating population aging in China. Care demand is dynamic due to various arrival ratepatterns, heterogeneous lengths of stay, health status, and balking and reneging behaviours, while supply depends on health/age/waiting-time-based priority queueing strategies. We develop a simulation-optimisation model that combines discrete event simulation, a bisection search algorithm and a feasibility detection procedure for this problem. Based on data from the Chinese Longitudinal Healthy Longevity Survey, the Ministry of Civil Affairs of China, and the queue system for senior care institutions in Shenzhen, the results show that the increasing arrival pattern saves operational costs and waiting time. The age-based-priority (ABP) strategy can reduce evaluation and waiting costs and prevent rent-seeking before application because it counts only older adult’ age. Balking helps to reduce reneging. Low ratio of caregivers to seniors will lead to significant underestimation of caregiver capacity. The ECS can purchase beds step by step, apply the ABP strategy for admission, release waiting information to induce balking behaviour, and hire part-time caregivers or rent service robots to reach the optimal plan while serving more older adults.