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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiaoyan Zhuo Han Huang Zhaoquan Cai Hui Hu |
| Copyright Year | 2015 |
| Description | Author affiliation: Sch. of Software Eng., South China Univ. of Technol., Guangzhou, China (Xiaoyan Zhuo; Han Huang) || Huizhou Univ., Huizhou, China (Zhaoquan Cai; Hui Hu) |
| Abstract | Nurse Rostering Problem (NRP) is one of NP - hard combinatorial optimization problems about the distribution of medical resources. In the past, there have been several proposed methods like heuristic algorithms and algorithms based on establishing rigorous mathematical models. Especially, the hybrid algorithm combined integer programming and evolutionary algorithm (IP+EA) have been proved to be effective for NRP. However, these methods are not efficient in dealing with large-scale NPR instances, like Chinese NRP. In order to overcome the premature convergence of IP+EA, we propose a hybrid evolutionary algorithm based on scout bee global search strategy. Inspired by the behavior of scouts in artificial bee colony algorithms, the global search is integrated into EA, which can lead the algorithm to escape from local optima. The experimental results indicate that, our proposed approach is more effective than several existing algorithms to solve the Chinese NRP. |
| Starting Page | 769 |
| Ending Page | 775 |
| File Size | 583773 |
| Page Count | 7 |
| File Format | |
| e-ISBN | 9781479974924 |
| DOI | 10.1109/CEC.2015.7256969 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-25 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | IP networks Search problems Optimization Evolutionary computation Algorithm design and analysis Heuristic algorithms Scheduling |
| Content Type | Text |
| Resource Type | Article |
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