A survey of quantum genetic algorithm for combinatorial optimization problems

摘要：

Combined with quantum computing and genetic algorithm, quantum genetic algorithm (QGA) shows considerable ability of parallelism. Experiments have shown that QGA performs quite well on TSP, job shop problem and some other typical combinatorial optimization problems. The other problems like nutritional diet which can be transformed into specific combinational optimization problem also can be solved through QGA smoothly. This paper sums up the main points of QGA for general combinatorial optimization problems. These points such as modeling of the problem, qubit decoding and rotation strategy are useful to enhance the convergence speed of QGA and avoid premature at the same time.

关键词： quantum genetic algorithm combinatorial optimization problem quantum computing traveling salesman problem

作者: WEI Fengmei ZHANG Janpei YANG Jing CHUYan

作者单位: College of Computer Science and Technology, Harbin Engineering University, China School of technolog College of Computer Science and Technology, Harbin Engineering University Harbin, China

会议类型: 国际会议

会议名称: 2010 4th International Conference on Intelligent Information Techonlogy Application(第四届智能信息技术应用国际学术研讨会 IITA 2010)

会议地点: 秦皇岛

会议语种:英文

页码: 177-180

在线出版日期: 2010-11-05（万方平台首次上网日期，不代表论文的发表时间）