Parallel processing of cooperative genetic algorithm for nurse scheduling

M. Ohki, S. Uneme, H. Kawano
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引用次数: 7

Abstract

This paper proposes an effective parallel algorithm for the cooperative genetic algorithm (CGA) to solve a nurse scheduling problem. The nurse scheduling is very complex task for a clinical director in a general hospital. Even veteran director needs one or two weeks to create the schedule. Besides, we extend the nurse schedule to permit the change of the schedule. This permission has explosively increased computation time for the nurse scheduling. We propose the new parallel algorithm to solve the problem. The parallel CGA has brought surprising effective results.
协同遗传算法在护士调度中的并行处理
针对护士调度问题,提出了一种有效的协同遗传算法并行算法。对综合医院的临床主任来说,护士调度是一项非常复杂的工作。即使是经验丰富的导演也需要一到两周的时间来制定时间表。此外,我们延长了护士的时间表,以允许时间表的变化。这一许可极大地增加了护士调度的计算时间。我们提出了一种新的并行算法来解决这个问题。并行CGA取得了令人惊讶的效果。
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