Multi-objective Robust Stochastic Planning and Scheduling of Healthcare Service Providers

这笔赠款提供资金，用于开发针对规划、调度、人员配置和分配(PSSA)问题的新模型和方法，这些问题具有多个目标，并且由于未来的不确定性而不可预测。此类问题经常出现在医疗行业，这将是重点应用领域。多个经常相互竞争的目标的例子有：患者安全和满意度、服务成本、护理的连续性、住院医师的教育目标和员工满意度。不确定性的例子包括病人的工作量和服务时间。将为医疗保健专业人员结合这一环境的独特特征为此类问题开发现实的数学模型。特别关注的是住院医师的日程安排。将开发用于求解这些模型的计算方法。特别是，将开发启发式方法来快速确定此类问题的良好候选解决方案。这些方法将在医疗保健设置的真实数据上进行测试。如果成功，这项研究的结果将使医疗保健提供者能够改善工作流程，并利用提供者的医务人员的技能。改善医学院住院医生的培训计划将是可能的，同时满足他们的住院医生要求。随着护理连续性的加强，患者满意度将会提高。为解决医疗保健中出现的问题而开发的计算方法也将适用于生产计划、供应链管理和车辆等广泛应用领域中出现的随机多目标整数规划模型。

This grant provides funding for developing novel models and methods for planning, scheduling, staffing, and assignment (PSSA) problems that have multiple objectives and are unpredictable because of future uncertainty. Such problems arise frequently in the healthcare industry, which would be the focus application area. Examples of multiple, often competing, objectives are: patient safety and satisfaction, cost of service, continuity of care, educational goals of the residents, and staff satisfaction. Examples of uncertainty are patient workload and service times. Realistic mathematical models will be developed for such problems for healthcare professionals incorporating the unique features of this setting. A particular focus will be on medical resident scheduling. Computational methods will be developed for solving these models. In particular, heuristic methods will be developed for quickly identifying good candidate solutions for such problems. These methods will be tested on realistic data from the healthcare setting.If successful, the results of this research will enable healthcare providers to improve work flow and to make utilize the skills of the provider's medical staff. Improved training schedules of medical school residents would be possible, while meeting their residency requirements. Patient satisfaction will improve as continuity of care is enhanced. The computational methods developed for solving problems arising in healthcare will also be useful for stochastic multi-objective integer programming models arising in a wide variety of application areas including production planning, supply chain management and vehicle.