| Summary: | 碩士 === 國立虎尾科技大學 === 資訊工程系碩士班 === 104 === In this thesis, the Cloud based Hybrid evolution algorithm for NP-Complete Pattern in Nurse Scheduling Problem (NSP) is proposed as the Software Computing as a Service (SCaaS). Due to the low birth rate, the human resource becomes the limited resource for job assignment. To find the optimal solution for staff scheduling becomes an important issue. The proposed system follows the definition of NSP and recognizes the possible problem of NP-Complete Pattern. Only the pattern is recognized as the NSP optimal problem, the proposed system can find the optimal solution. Then, the different types of evolutionary algorithm in evolution steps are integrated. Based on the proposed Feedback Assistance method, the suitable evolution steps of the evolutionary algorithm can be dynamically decided and executed. Similar to the Tasktracker and Jobtracker in cloud, all the computing load can be divided and distributed. The simulation results show that the proposed hybrid evolution algorithm can find the optimal solution with about 50% less evolution generations.
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