论文标题
使用进化多样性优化计算患者入院计划问题的高质量解决方案
Computing High-Quality Solutions for the Patient Admission Scheduling Problem using Evolutionary Diversity Optimisation
论文作者
论文摘要
一组解决方案中的多元化已成为进化计算社区中的热门研究主题。事实证明，它有助于以多种方式优化问题，例如计算各种高质量的解决方案并获得对不完善建模的鲁棒性。在文献中，我们首次适应了对现实世界中的组合问题的进化多样性优化，即患者的入学计划。我们引入了一种进化算法，以在每种溶液质量的一组解决方案中实现结构多样性。我们还引入了一个突变操作员，偏向于多样性最大化。最后，我们通过模拟证明了多样性对上述问题的重要性。
Diversification in a set of solutions has become a hot research topic in the evolutionary computation community. It has been proven beneficial for optimisation problems in several ways, such as computing a diverse set of high-quality solutions and obtaining robustness against imperfect modeling. For the first time in the literature, we adapt the evolutionary diversity optimisation for a real-world combinatorial problem, namely patient admission scheduling. We introduce an evolutionary algorithm to achieve structural diversity in a set of solutions subjected to the quality of each solution. We also introduce a mutation operator biased towards diversity maximisation. Finally, we demonstrate the importance of diversity for the aforementioned problem through a simulation.
