A Novel Quantum-inspired Genetic Algorithm with Expanded Solution Space

摘要：

In this paper, we present a novel quantum-inspired genetic algorithm with expanded solution space. Based on the double chains quantum genetic algorithm (DCQGA), we have expanded the solution space by increasing the number of solution space transformation functions. And we propose a novel method for quantum rotation gates update by using the sign function and the gradient of objective function. With this method we can automatically determine the direction of quantum rotation gate and adaptively adjust the magnitude of quantum rotation gate. Through experimenting on 2 benchmark problem in the optimization literature: Rosenbrock function and Schaffers F6 function, we demonstrate that our expanded solution space quantum genentic algorithm (ESSQGA) has achieved more satisfactory results than DCQGA and common genetic algorithm.

作者: Renjie Liao Xueyao Wang Zengchang Qin

作者单位: School of Automation Science and Electrical Engineering Beihang University Beijing 100191

会议类型: 国际会议

会议名称: 2010 Second International Conference on Intelligent Human-Machine Systems and Cybernetics(第二届智能人机系统与控制论国际学术会议 IHMSC 2010)

会议地点: 南京

会议语种:英文

页码: 531-534

在线出版日期: 2010-08-26（万方平台首次上网日期，不代表论文的发表时间）