The planning of hospital beds is among the most debated problems in healthcare. Despite being an important issue, many initiatives have failed to sustain services improvements, resulting in high costs and also high refusal rates. The stochastic problem involves conflicting criteria, therefore, we propose a Simulation-Optimisation approach to solve it. The Evolutionary Algorithm NSGA-II drives the process, and the solutions are validated and evaluated via Discrete Event Simulation. An application is performed in one of the health regions of the state of Minas Gerais, Brazil, where the public health system assists nearly 80% of the patients. The results pointed out that the proposed approach could find efficient and feasible solutions for the problem. Therefore, it is a good alternative to empirical methods currently used in Brazil to set hospital beds allocation.

病床的规划是医疗保健中争议最大的问题之一。尽管这是一个重要的问题，但许多举措仍未能维持服务的改进，从而导致高成本和高拒绝率。随机问题涉及标准冲突，因此，我们提出了一种仿真优化方法来解决该问题。进化算法NSGA-II驱动该过程，并通过离散事件仿真对解决方案进行验证和评估。在巴西米纳斯吉拉斯州的一个健康地区进行了申请，该地区的公共卫生系统为近80％的患者提供了帮助。结果表明，该方法可以为该问题找到有效可行的解决方案。因此，