期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 41, 期 16, 页码 7248-7258出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2014.05.053
关键词
Clonal selection algorithm; Bi-direction quantum crossover; Traveling salesman problem; Holes machining path planning problem; Multi-objective optimization
类别
资金
- Qinglan Project of Jiangsu Province
- Project of Jiangsu Overseas Research & Training Program for University Prominent Young & Middle-aged Teachers and Presidents
- Natural Science Fund for Colleges and Universities in Jiangsu Province [13KJB520002]
- Natural Science Foundation of Jiangsu Province [BK2012663]
- Jiangsu Institute of Marine Resources [JSIMR201338]
In order to improve the performance of quantum interference crossover, a bi-direction quantum crossover is proposed based on the quantum jump theory. The proposed crossover is inspired by the principle of quantum mechanics. That is, when an electron drops from a higher energy level to a lower energy level, energy is released by the atom. Also, energy is absorbed when it moves from a lower energy level to a higher energy level. The bi-direction quantum crossover is combined with clonal selection algorithm (CSA) to further enhance the performance of CSA. The effectiveness of the method is tested on a class of traveling salesman problems (TSP) and engineering practical problems of holes machining path planning (HMPP). Experimental results show that the proposed algorithm achieves a good balance between exploration and exploitation, and outweighs other CSAs and heuristic algorithms in terms of convergence speed and robustness. (C) 2014 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据