A difficult optimization problem called the nurse rostering problem is solved by choosing groups of nurses and allocating sets of shifts to them. As a result, creating schedules for healthcare workers is typically a challenging issue. The "Tissue like P System TLPS" is a new technique that is proposed in the current study. For resolving the nurse rostering issue at the National University of Malaysia Medical Center, also known as University Kebangsaan Malaysia in Malaysian. It is a genuine problem that has historically been dealt with manually and is tough to fix. The key issue is distributing responsibilities to a group of nurses while keeping in mind the laws and guidelines. We showed that the suggested algorithm had a considerable impact. Additionally, a comparison of the proposed algorithm’s performance using traditional approaches on the same dataset revealed that the proposed approach was noticeably more efficient.

通过选择护士组并向他们分配轮班组来解决称为护士排班问题的困难优化问题。因此，为医护人员制定时间表通常是一个具有挑战性的问题。“Tissue like P System TLPS”是当前研究中提出的一项新技术。解决马来西亚国立大学医学中心（马来西亚国立大学医学中心）的护士排班问题。这是一个真正的问题，历来都是手动处理的，而且很难修复。关键问题是将责任分配给一组护士，同时牢记法律和准则。我们表明所建议的算法具有相当大的影响。此外，在同一数据集上使用传统方法对所提出的算法的性能进行比较表明，所提出的方法明显更有效。