KaHo Sint-Lieven, Information Technology, Gent, Belgium.
Artif Intell Med. 2010 Jan;48(1):61-70. doi: 10.1016/j.artmed.2009.09.001. Epub 2009 Oct 14.
We describe a patient admission scheduling algorithm that supports the operational decisions in a hospital. It involves efficiently assigning patients to beds in the appropriate departments, taking into account the medical needs of the patients as well as their preferences, while keeping the number of patients in the different departments balanced.
Due to the combinatorial complexity of the admission scheduling problem, there is a need for an algorithm that intelligently assists the admission scheduler in taking decisions fast. To this end a hybridized tabu search algorithm is developed to tackle the admission scheduling problem. For testing, we use a randomly generated data set. The performance of the algorithm is compared with an integer programming approach.
The metaheuristic allows flexible modelling and presents feasible solutions even when disrupted by the user at an early stage in the calculation. The integer programming approach is not able to find a solution in 1h of calculation time.
我们描述了一种患者入院安排算法，该算法支持医院的运营决策。它涉及到有效地将患者分配到适当科室的床位，既要考虑患者的医疗需求，也要考虑到他们的偏好，同时还要保持各科室的患者人数平衡。
由于入院安排问题的组合复杂性，需要有一种算法能够智能地帮助入院安排者快速做出决策。为此，开发了一种混合禁忌搜索算法来解决入院安排问题。为了进行测试，我们使用了一个随机生成的数据集。将算法的性能与整数规划方法进行了比较。
元启发式算法允许灵活建模，并在计算的早期阶段即使被用户中断也能提供可行的解决方案。整数规划方法在 1 小时的计算时间内无法找到解决方案。
