.png){kind=icon}
返回
A novel quantum swarm evolutionary algorithm and its applications
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2006.10.001.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, a novel quantum swarm evolutionary algorithm (QSE) is presented based on the quantum-inspired evolutionary algorithm (QEA). A new definition of Q-bit expression called quantum angle is proposed, and an improved particle swarm optimization (PSO) is employed to update the quantum angles automatically. The simulated results in solving 0-1 knapsack problem show that QSE is superior to traditional QEA. In addition, the comparison experiments show that QSE is better than many traditional heuristic algorithms, such as climb hill algorithm, simulation anneal algorithm and taboo search algorithm. Meanwhile, the experimental results of 14 cities traveling salesman problem (TSP) show that it is feasible and effective for small-scale TSPs, which indicates a promising novel approach for solving TSPs. (c) 2006 Elsevier B.V. All rights reserved.
Keyword:
quantum swarm evolutionary algorithm
quantum-inspired evolutionary algorithm
particle swarm optimization
knapsack problem
traveling salesman problem
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
机构
暂无机构信息
引用论文
Stimuli-responsive nanoscale drug delivery system for epilepsy theranostics刺激响应型纳米药物递送系统用于癫痫诊疗学.png)
ACTA BIOMATERIALIA
ACTA BIOMATERIALIAIF9.6
PREAI
分享收藏 没有更多内容
没有更多内容