Cooperative Control Model of Geographically Distributed Multi-teamAgile Development Based on MO-CSO

Jijiao Jiang, X. Yang, Ming Yin
{"title":"Cooperative Control Model of Geographically Distributed Multi-teamAgile Development Based on MO-CSO","authors":"Jijiao Jiang, X. Yang, Ming Yin","doi":"10.1145/3241748.3241767","DOIUrl":null,"url":null,"abstract":"Be aimed at the question of Geographically Distributed Collaborative Development (GDCD) parallel tasks which are difficult to coordinate control, this paper proposes a collaborative scheduling model for agile development based on Multi-Objective Cat Swarm Optimization (MO-CSO). The Cat Swarm Optimization (CSO) performs global search and local optimization with its good convergence speed and Pareto search capability, so that the model can search the optimal solution efficiently and quickly. Under the condition of limited resources, the allocation of resources and tasks is reasonably carried out to achieve a dynamic and intelligent scheduling process.And simulation experiments on the case are carried out by MATLAB, and the effectiveness of the algorithm is verified, which can quickly meet the needs of dynamic agility development.","PeriodicalId":339129,"journal":{"name":"Proceedings of the 2018 2nd International Conference on E-Education, E-Business and E-Technology","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2018 2nd International Conference on E-Education, E-Business and E-Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3241748.3241767","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Be aimed at the question of Geographically Distributed Collaborative Development (GDCD) parallel tasks which are difficult to coordinate control, this paper proposes a collaborative scheduling model for agile development based on Multi-Objective Cat Swarm Optimization (MO-CSO). The Cat Swarm Optimization (CSO) performs global search and local optimization with its good convergence speed and Pareto search capability, so that the model can search the optimal solution efficiently and quickly. Under the condition of limited resources, the allocation of resources and tasks is reasonably carried out to achieve a dynamic and intelligent scheduling process.And simulation experiments on the case are carried out by MATLAB, and the effectiveness of the algorithm is verified, which can quickly meet the needs of dynamic agility development.
基于MO-CSO的地理分布式多团队敏捷开发协同控制模型
针对地理分布式协同开发(GDCD)并行任务难以协调控制的问题,提出了一种基于多目标猫群优化(MO-CSO)的敏捷开发协同调度模型。CSO算法具有良好的收敛速度和Pareto搜索能力,可以进行全局搜索和局部优化,使模型能够高效、快速地搜索到最优解。在资源有限的情况下,合理地进行资源和任务的分配,实现动态智能调度过程。并利用MATLAB对该案例进行了仿真实验,验证了算法的有效性,能够快速满足动态敏捷性开发的需要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信