Scheduling and Resource Allocation for Improving Service and Operations Management: Modelling, Solution Methods and Applications (especially in Healthcare)

用于改进服务和运营管理的调度和资源分配：建模、解决方案方法和应用（特别是在医疗保健领域）

• 批准号: RGPIN-2018-06219
• 负责人: Begen, Mehmet
• 金额: $ 1.89万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=681661
• 关键词: Scheduling; Resource; Allocation; Improving; Service

This proposal will develop models and solution methods to improve scheduling and resource allocation decisions in service and operations management applications, especially in healthcare. The goal is to achieve better service levels (e.g., shorter wait times (until service day), timely service (at the say of service)), lower cost to service/product providers (e.g., less overtime, lower capacity requirements) and better utilization of resources. There are many real-world applications for the proposal's models and methods in different industries such as service, healthcare and manufacturing. Two main areas are considered: *** Combined appointment and advance scheduling (CAAS)*** Generalized multi resource scheduling (GMRS)***The aim of CAAS is to find an optimum schedule for a service system where jobs (e.g., customers, patients) arrive to the system randomly (arrival times, quantity, priority and job types) and they are assigned a service day. Jobs wait until the day of the service and job processing times are stochastic. Jobs are processed in a given order in the day of the service. The goal is to find a scheduling policy that minimizes total expected cost (before the day of the service and during the day of the service). The scheduling policy consists of determining day of the service (date) and time of the service (appointment time for a given day of the service). The cost consists of wait time until the day of the service, wait time during the day of the service, idle time of the server, and overtime of the server. I will seek answers to:*** How to model and solve the CAAS problem?*** How to solve the CAAS problem with a different objective criterion other than minimizing the expected value (e.g., a percentile of the cost)? *** How to determine an optimal sequence of jobs for daily processing? *** How to add an end-resource where all jobs stay for some time after they are processed and before they leave the system?***The goal of GMRS is to develop models and solution methods to find a sequencing schedule minimizing processing costs for a given set of jobs (e.g., surgeries) to be processed on multiple machines (e.g., operating rooms) by multiple sets of resources (e.g., surgeons and anesthetists). The output of such a model is the optimum number of machines and optimum job processing schedule (with assigned resources) minimizing the total cost of running machines (regular time and overtime). When a job is processed on a machine, each resource needs to work in a sequential manner and lag times (e.g., a surgeon must wait until preparation and anesthesia are done) between different resources are considered. Further complication is that jobs have different types (e.g., surgical specialty), and resources are based on job types. I will search answers for the following questions: *** How to model and solve GMRS?*** How to model and solve a stochastic version GMRS, i.e., job durations stochastic?*** How to model and solve GMRS with an end-resource?

该提案将开发模型和解决方案，以改善服务和运营管理应用程序中的调度和资源分配决策，特别是在医疗保健领域。目标是实现更好的服务级别（例如，较短的等待时间（直到服务日）、及时的服务（在服务的发言中）），服务/产品提供者的较低成本（例如，更少的加班时间、更低的能力需求）和更好地利用资源。该提案的模型和方法在不同行业有许多实际应用，如服务，医疗保健和制造业。审议了两个主要领域：* 组合预约和提前调度（CAAS）* 广义多资源调度（GMRS）* CAAS的目的是为服务系统找到最优调度，其中作业（例如，顾客、病人）随机地（到达时间、数量、优先级和工作类型）到达系统，并且为他们分配服务日。 作业等待直到服务的一天，作业处理时间是随机的。在服务当天，工作按给定的顺序进行处理。我们的目标是找到一个调度策略，最大限度地减少总的预期成本（前一天的服务和服务期间的一天）。调度策略包括确定服务日（日期）和服务时间（指定服务日的预约时间）。成本包括服务当天的等待时间、服务当天的等待时间、服务器的空闲时间和服务器的超时时间。我将寻求答案：* 如何建模和解决CAAS问题？*如何用不同的客观标准解决CAAS问题，而不是最小化期望值（例如，成本的百分之一）。* 如何确定日常处理的最佳作业顺序？* 如何添加一个终端资源，所有作业在处理后离开系统前都会停留一段时间？* GMRS的目标是开发模型和求解方法，以找到最小化给定作业集（例如，手术）在多台机器上处理（例如，手术室）通过多组资源（例如，外科医生和麻醉师）。这样一个模型的输出是最佳的机器数量和最佳的作业处理时间表（分配资源），使机器运行的总成本（正常时间和加班）最小化。当在机器上处理作业时，每个资源都需要以顺序的方式工作，并且滞后时间（例如，外科医生必须等待直到准备和麻醉完成）。更复杂的是作业具有不同的类型（例如，外科专业），资源基于工作类型。我将搜索以下问题的答案：* 如何建模和求解GMRS？*如何建模和求解随机版本的GMRS，即，作业持续时间随机？*如何建模和解决具有终端资源的GMRS？