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Medical doctor rostering problem in a hospital emergency department by means of genetic algorithms

机译:遗传算法在医院急诊科医师排班问题

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Organising shifts, or work rosters, is a problem that affects a large number of businesses where employees are subject to some kind of work rotation. Researchers in the fields of Operations Research and Artificial Intelligence have resorted to several different optimisation systems to solve the problem. The motivation for the medical-staff shift-rotation research presented in this paper stems from the needs of an actual hospital emergency department (HED) and from the observed growing staff of these services in Spain. The problem approach, which has been hardly dealt with in the literature, intends to automate the creation of time-tables by applying genetic algorithms (GAs) in an actual HED. HEDs work organisation becomes different because of the combination of shifts and 24-h duties. After knowing the HED workers' requirements (which will allow to identify the hard and soft constraints imposed to the problem) and after defining the adequate encoding to be used in the solutions, a heuristic-schedule builder -designed ad hoc to satisfy the hard constraints - produces an initial population of feasible solutions. Afterwards, iteratively, GA obtains new generations of feasible individuals, thanks to the use of a specific crossover operator, based in the exchange of whole work weeks, that operates together with a repair function. Once the optimum is reached, the results obtained are discussed as a function of the degree of satisfaction of the constraints under which the system operates and of the adaptability of the system as the constraints vary.
机译:组织轮班或工作花名册是一个问题,它影响到许多公司的员工需要进行某种工作轮换。运筹学和人工智能领域的研究人员已采用几种不同的优化系统来解决该问题。本文提出的医务人员轮换研究的动机来自于实际的医院急诊科(HED)的需求以及在西班牙观察到的这些服务不断增长的人员。问题方法在文献中几乎没有涉及,旨在通过在实际的HED中应用遗传算法(GA)来自动创建时间表。由于轮班和24小时职责的结合,HED的工作组织变得不同。在了解了HED工作人员的要求(这将允许确定对问题施加的硬约束和软约束)并定义了将在解决方案中使用的适当编码之后,启发式计划生成器设计了临时方案来满足硬约束-产生大量可行的解决方案。之后,由于在整个工作周的交换中使用了特定的交叉运算符,因此GA可以迭代地获得新一代可行的人,该运算符与维修功能一起工作。一旦达到最佳,就将讨论所获得的结果,作为对系统运行所依据的约束的满足程度以及随约束变化而变化的系统适应性的函数。

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