Optimization methods for complex personnel shift scheduling problems

Kronos加拿大系统公司将劳动力调度软件商业化，服务于全球1100多家组织，其中包括加拿大的107家组织。该软件允许确定员工在各个领域的工作时间表，包括零售，医疗保健，休闲和酒店，以及制造业。人员轮班调度是一个复杂的优化问题，它涉及确定每个可用员工的工作日，每个工作日的确切班次，以及每个班次要执行的工作，以便最好地满足员工对每个工作的需求。在Kronos，目前的优化算法旨在解决计划版本的人员调度问题。在这个项目中，我们建议增强它的能力，并探索解决人员调度问题的复杂版本的替代算法，即，当不可预见的事件发生时需要修改计划调度的重新调度，考虑需求变化和潜在员工缺勤的鲁棒调度，以及考虑部门之间或站点之间可能的员工转移的多部门/多站点调度。我们的主要目标是开发一种有效的算法来解决这些问题变体的实际实例。为此，我们将进行数学建模、数据分析和方法开发。

Kronos Canadian Systems Inc. commercializes the Workforce Scheduler software to more than 1,100 organizations across the world, including 107 in Canada. This software allows to determine the work schedules of employees in various domains including retail, healthcare, leisure and hospitality, and manufacturing. Personnel shift scheduling is a complex optimization problem that involves determining for each available employee his working days, the exact shift to work on each working day, and the job(s) to perform in each shift, in order to cover at best the demand in employees for each job. At Kronos, the current optimization algorithm aims at solving a planning version of the personnel scheduling problem. In this project, we propose to enhance its capabilities and to explore alternative algorithms for solving complex versions of the personnel scheduling problem, namely, rescheduling that requires revising planned schedules when unforeseen event occur, robust scheduling that takes into account demand variation and potential employee absenteeism, and multi-department/multi-site scheduling that considers possible employee transfers between departments or between sites. Our main objective is to develop an efficient algorithm for solving practical instances of each of these problem variants. To do so, we will perform mathematical modeling, data analysis, and methodological developments.