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CONSTRAINT SOVLING ENGINE BASED NURSE ROSTERING WITH INTELLIGENT BACKTRACKING | Science Publications

机译:基于约束的基于智能引擎的基于引擎的护士排班|科学出版物

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> Efficient utilization of time and effort is essential in Personnel scheduling problems to evenly balance the workload among the people and attempt to satisfy the personnel preferences. In Constraint Satisfaction Problem based scheduling problems, when a branch of the search fails the backtracking search algorithm back up to the preceding variable and try a different value for it. So here the most recent decision point is revisited. Its run-time complexity for most nontrivial problems is still exponential. A solution is intelligent backtracking scheme in which backtracking is done directly to the variable that caused the failure. This study proposes Constraint Satisfaction Problem based Nurse Rostering using Intelligent Backtracking approach. The proposed Minimal Critical Set based Intelligent Backtracking (MCS-IBT) algorithm incorporates Critical Set detection which is followed by Minimal Critical Set reduction in order to reduce the search space for nurse rostering. MCS_IBT overcomes missing good MCSs by visiting optimal number of sets. This study finds its applications in scheduling, temporal reasoning, graph problems, floor plan design, the planning of genetic experiments and the satisfiability problems. The implemented system is tested on the real life data from the hospital and the results shown remarkable performance.
机译: >有效地利用时间和精力在人员调度问题中至关重要,这样才能平衡人员之间的工作量并尝试满足人员的偏好。在基于约束满足问题的计划问题中,当搜索的一个分支失败时,回溯搜索算法将备份到前一个变量,并为其尝试一个不同的值。因此,这里重新讨论了最新的决策点。对于大多数非平凡的问题,它的运行时复杂度仍然是指数级的。一种解决方案是智能回溯方案,其中直接对导致失败的变量进行回溯。这项研究提出了基于约束满意问题的护士排班,采用智能回溯方法。所提出的基于最小临界集的智能回溯(MCS-IBT)算法结合了临界集检测,然后进行最小临界集缩减,以减少用于护士排班的搜索空间。 MCS_IBT通过访问最佳集合数来克服缺少好的MCS的问题。本研究发现了其在调度,时间推理,图形问题,平面布置图设计,基因实验计划和可满足性问题中的应用。该实施系统对医院的真实生活数据进行了测试,结果显示了出色的性能。

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