Optimization methods for complex personnel shift scheduling problems

复杂人员排班问题的优化方法

• 批准号: 468716-2014
• 负责人: Desaulniers, Guy
• 金额: $ 7.88万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=563009
• 关键词: Optimization; methods; complex; personnel; shift

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.

Kronos Canadian Systems Inc.将劳动力调度程序软件商业化到全球1,100多个组织，包括加拿大的107个组织。该软件允许确定各个领域员工的工作时间表，包括零售，医疗保健，休闲和款待以及制造业。人事班次调度是一个复杂的优化问题，涉及为每个可用员工确定他的工作日，每个工作日工作的确切转变以及在每次班次中执行的工作，以充分满足每项工作的员工需求。在Kronos，当前的优化算法旨在解决人员调度问题的计划版本。在这个项目中，我们建议提高其能力，并探索替代算法来求解人员调度问题的复杂版本，即，重新安排需要在不预见的事件中进行修改计划的时间表，并在不预见的情况下进行强大的时间安排，以考虑到需求变化和可能的多项派遣/多e Mutifeers insige interime insigh the Multie countfort andime countfort and countfort countfort countfort countfort countfort countfort countfort countfort and countfort countfort coustfore countfort and coustf and coustfors countfort and coustf an站点。我们的主要目的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，我们将执行数学建模，数据分析和方法论发展。