Using social spider optimisation to solve nurse scheduling problem
| dc.contributor.author | Kogulabalan Gunasegaran | |
| dc.date.accessioned | 2021-04-23T01:54:00Z | |
| dc.date.available | 2021-04-23T01:54:00Z | |
| dc.date.issued | 2017-06 | |
| dc.description.abstract | Creating a nurse schedule has been a tough job for many healthcare management. The management takes very long time to construct a schedule that satisfies the hospital rules and nurses’ preferences. Diverse types of techniques have been implemented to obtain schedule within short period of time. However, all the techniques failed to yield the best schedule within the stipulated time. Hence, in this project I propose a technique called Social Spider Optimisation (SSO) algorithm to solve Nurse Scheduling Problem (NSP). SSO is a newly found method discovered by researchers, but it has already proven to be fast and reliable method based on the previous researches. The proposed model satisfies both hospital’s rules and the nurses’ preferences. The results obtained from this model are beyond satisfying as the best solution has been yielded easily within small time frame. From the best solution obtained from one of the 20 runs carried out, the convergence time for Level 1, Level 2, Level 3 and Level 4 are 41.98s, 78.49s, 70.94s and 79.39s respectively. All the trendline for four levels has reached their convergence limit before reaching the maximum iteration number. In Level 1, the trendline converges before reaching 1500th iteration. In Level 2, the trendline has reached the convergence limit before reaching 3000th iteration. The trendlines in Level 3 and Level 4 also converged before reaching their maximum iteration numbers, 3500 and 4500 respectively. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/13090 | |
| dc.language.iso | en | en_US |
| dc.subject.lcsh | Nurse administrators | |
| dc.title | Using social spider optimisation to solve nurse scheduling problem | en_US |
| dc.type | Other | en_US |
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