24小时热门版块排行榜    

查看: 457  |  回复: 1

injt19891011

新虫 (初入文坛)

[求助] 请问这篇文章检索没? 已有1人参与

PLS help!

title:The Performance Research on Solving TSP by Four Typical AI Algorithms
Journal: <BioTechnology: An Indian Journal>
Author: Zhengqiang JIANG,……

谢谢!
回复此楼

» 猜你喜欢

» 本主题相关价值贴推荐,对您同样有帮助:

已阅   回复此楼   关注TA 给TA发消息 送TA红花 TA的回帖

fallsoft

金虫 (正式写手)

【答案】应助回帖

★ ★ ★ ★ ★
injt19891011(杈杈代发): 金币+5, Thanks very much! 2014-04-26 20:09:18
Accession number:       
20141317528604
        Title:        The performance research on solving TSP by four typical AI algorithms
        Authors:         Wu, Yue1 Email author wuyuenet@wo.com.cn; Jiang, Zheng-Qiang1 Email author injt19891011@126.com
        Author affiliation:        1 School of Logistics, Beijing Wuzi University, Beijing 101149, China
        Source title:        BioTechnology: An Indian Journal
        Abbreviated source title:        Biotechnol. An Indian J.
        Volume:        8
        Issue:        9
        Issue date:        2013
        Publication year:        2013
        Pages:        1234-1239
        Language:        English
        ISSN:         09747435
        Document type:        Journal article (JA)
        Publisher:        Trade Science Inc
        Abstract:        Travelling Salesmen Problem (VRP) has an important theoretical value and practical significance in mathematical and logistics field. It's a typical NPHard problem, and artificial intelligent (AI) Algorithm has been already proven to be a very effect way in solving this problem. This paper carried out the performance research on solving TSP by four typical AI algorithms after in-depth analyzed the TSP and these four algorithms (genetic algorithm, particle swarm optimization algorithm, simulated annealing algorithm and ant colony algorithm). This paper verified the TSP solving performance by China travelling salesmen problem experiments and MATLAB programming. The results showed that: considering the average iteration time, SA < PSO< ACA <GA; considering the optimal route length, GA<ACA<SA<PSO; and considering the iterative time to obtain optimal route, SA<ACA<PSO<GA. © 2013 Trade Science Inc. - INDIA.
        Number of references:        12
        Main heading:         Problem solving
        Controlled terms:         Genetic algorithms  -  Iterative methods  -  Particle swarm optimization (PSO)
        Uncontrolled terms:         AI algorithms  -  Ant colony algorithms  -  Artificial intelligent  -  Particle swarm optimization algorithm  -  Performance research  -  Simulated annealing algorithms  -  Solving performance  -  Travelling salesman
        Classification code:         723 Computer Software, Data Handling and Applications -  921 Mathematics -  921.6 Numerical Methods
        Database:        Compendex
                Compilation and indexing terms, © 2013 Elsevier Inc.
2楼2014-04-25 18:22:11
已阅   回复此楼   关注TA 给TA发消息 送TA红花 TA的回帖
相关版块跳转 我要订阅楼主 injt19891011 的主题更新
信息提示
请填处理意见