Integrated Personnel Scheduling in the Service Industry

服务业综合人员调度

• 批准号: 0218701
• 负责人: Jonathan Bard
• 金额: $ 9.86万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-15 至 2004-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0218701&HistoricalAwards=false
• 关键词: Integrated; Personnel; Scheduling; Service; Industry

The principal goal of this project is to develop an integrated decision support system that can be used by the service industry to better meet their long-term, mid-range, and day-to-day staffing needs. At each of these levels, the underlying problems will be modeled as large-scale integer programs and solved with a combination of exact methods and heuristics. A significant portion of the research is aimed at devising efficient solution algorithms. An associated objective is to develop new decomposition techniques and bounding schemes. Because many of the subproblems that arise at each of these levels have yet to be addressed by the research community, it is likely that additional modeling will be required to deal with qualitative issues, uncertainty, and the intricate nature of the constraints that inform practical applications. The methodologies developed will be implemented with an eye toward computational efficiency and robustness in the face of uncertainty. Expected results include: (1) the development of improved solution methods for personnel planning and scheduling in the service industry; (2) a greater understanding of modeling issues with respect to weekly tour generation and disruption management; (3) theoretical and practical characterizations of the performance of related algorithms; and (4) the design of an integrated decision support system. Effective personnel scheduling has become one of the primary means by which service enterprises remain competitive. Unlike manufacturing where standard shifts and days off are the rule, service organizations operate up to 24 hours a day, 7 days a week and face widely varying demand. Poor staff schedules can lead to an oversupply of workers with too much idle time, or an undersupply with customer dissatisfaction and a resultant loss of business. Stated alternatively, an important goal of this project is to find robust schedules for a nonhomogeneous workforce. The general problem faced by management is to meet daily staffing requirements at minimum cost without violating labor agreements, company policies, and government regulations. At the long-term planning level, consideration must be given to issues that determine the size and composition of the permanent workforce. At the weekly level, critical resources must be tracked and schedules updated to meet changes in demand. Real-time control come into play at the day-to-day level where absenteeism, equipment failures, and other disruptions call for online rescheduling.

该项目的主要目标是开发一个可供服务行业使用的综合决策支持系统，以更好地满足其长期、中期和日常的人员配置需求。 在每个级别，底层问题都将被建模为大规模整数程序，并通过精确方法和启发式的组合来解决。 研究的很大一部分旨在设计有效的解决算法。 一个相关的目标是开发新的分解技术和边界方案。 由于研究界尚未解决每个级别上出现的许多子问题，因此可能需要额外的建模来处理定性问题、不确定性以及影响实际应用的约束的复杂性。 所开发的方法将着眼于面对不确定性时的计算效率和鲁棒性。 预期成果包括：（1）开发改进的服务业人员计划和调度解决方法； (2) 更好地理解与每周旅游生成和中断管理有关的建模问题； (3)相关算法性能的理论和实践表征； (4)综合决策支持系统的设计。有效的人员调度已成为服务企业保持竞争力的主要手段之一。 与按标准轮班和休息日为规则的制造业不同，服务组织每周 7 天、每天 24 小时运营，面临着广泛变化的需求。 糟糕的员工排班可能会导致员工供过于求，闲置时间过多，或者导致供应不足，导致客户不满意，从而导致业务损失。 换句话说，该项目的一个重要目标是为非同质的劳动力找到可靠的时间表。管理层面临的普遍问题是在不违反劳动协议、公司政策和政府法规的情况下，以最低成本满足日常人员配备需求。 在长期规划层面，必须考虑决定长期劳动力规模和构成的问题。 在每周级别，必须跟踪关键资源并更新时间表以满足需求的变化。 实时控制在日常层面发挥作用，缺勤、设备故障和其他中断需要在线重新安排。