摘要
作为典型的NP完全问题，大学排课问题在教务管理系统中非常重要。该文通过对大学排课问题的数学模型的分析，运用量子遗传算法进行求解。实验结果表明，利用量子遗传算法求解大学排课问题要优于使用遗传算法。
As the classic NP-Complete Problem, University Timetable Problem is very important to the academic course scheduling management system. In this paper, the mathematic model of university timetable problem is analyzed, and the quantum-inspired genetic algorithm is used to solve it. The results of experiments show that the quantum-inspired genetic algorithm is more effective to genetic algorithm in solving the university timetable problem.
作者
曹敏志
CAO Min-zhi （Hunan Biological and Electromechanical Polytechific, Changsha 410127, China）
出处
《电脑知识与技术》
2010年第02Z期1174-1175,1178,共3页
Computer Knowledge and Technology
关键词
大学排课问题
NP难问题
遗传算法
量子遗传算法
university timetable problem
NP-hard problem
genetic algorithm
quantum-inspired genetic algorithm
