Quantum-inspired Genetic Evolutionary Algorithm For Course Timetabling

被引：2
|
作者：
Zheng, Yu [1 ,2 ]
Liu, Jing-fa [2 ]
Geng, Wue-hua [2 ]
Yang, Jing-yu [1 ]
机构：
[1] Nanjing Univ Sci & Technol, Dept Comp Sci, Nanjing, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing, Peoples R China
来源：
THIRD INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING | 2009年
基金：
美国国家科学基金会;
关键词：
Course timetabling problem; QEA; quantum computing; combinatorial optimization;
D O I：
10.1109/WGEC.2009.164
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The course timetabling problem (CTP), as a typical combinatorial optimization problem (COP), has been proved to be NP-Complete. Due to its complexity, the general genetic algorithm converges slowly and easily converges to local optima. A novel quantum-inspired evolutionary algorithms (QEA) is put forward for the CTP. The QEA uses genetic operators of Q-bit as well as updating operator of quantum gate which is introduced as a variation operator to drive the individuals toward better solutions. The experimental results and comparisons demonstrate that the QEA not only perform significantly better convergence rate than the general genetic algorithm but also can provide a set of high quality timetables.
引用
收藏
页码：750 / +
页数：2
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