用遗传算法进行门诊调度:突变运营者的力量
Veronika Gombás1, Péter Bálint Scsibrán1, Tibor Dulai1
1Department of Computer Science and Systems Technology, University of Pannonia, Veszprem, Hungary.
Studies in health technology and informatics
|April 24, 2025
概括
一个专门的遗传算法通过使用指数突变运算符显著改善了门诊调度. 这种方法提高了效率,并在复杂的调度任务中最大限度地减少了考试完成时间.
科学领域:
- 运营研究 运营研究
- 计算机科学 计算机科学
- 医疗保健管理的管理
背景情况:
- 门诊安排具有相当大的复杂性和时间要求.
- 包括遗传算法在内的优化方法已经被探索,以应对这些挑战.
研究的目的:
- 开发一个特定任务的遗传算法,用于门诊安排.
- 评估各种突变运算子对算法性能的影响.
- 尽量减少预定考试的最早完成时间.
主要方法:
- 设计并比较了随机和两个启发式突变运算符.
- 在四个不同的调度场景中评估了运营商的表现.
- 专注于优化考试安排.
主要成果:
- 指数突变运算符在所有场景中都表现出卓越的性能.
- 在100%的简单任务和74.5%的复杂任务中实现了最佳时间表.
- 显著优于随机和多项式突变运算符.
结论:
- 突变运营者的选择对门诊调度中的遗传算法效率产生了重大影响.
- 将突变运算符定制为目标函数可以大大提高调度性能.
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