大学实验室课程安排的共生生物搜索算法

C. Pickerling, Hendrawan Armanto, E. Setyaningsih
{"title":"大学实验室课程安排的共生生物搜索算法","authors":"C. Pickerling, Hendrawan Armanto, E. Setyaningsih","doi":"10.1109/CAIPT.2017.8320698","DOIUrl":null,"url":null,"abstract":"Numerous research has been done on scheduling, however only a few results an optimal schedule. Thus are schedule is made manually. The most frequently used algorithm for scheduling problem is genetic algorithm, but in this research we used Symbiotic Organisms Search Algorithm. This algorithm is used to simulate the behavior of organisms in their environment because of their dependence on the survival of the other species. We tested the algorithm for scheduling laboratory activities and after a number of trials, we concluded that this algorithm is able to provide an optimal solution for scheduling problem with 87.17% accuracy.","PeriodicalId":351075,"journal":{"name":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Symbiotic organisms search algorithm for scheduling laboratory sessions in University\",\"authors\":\"C. Pickerling, Hendrawan Armanto, E. Setyaningsih\",\"doi\":\"10.1109/CAIPT.2017.8320698\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Numerous research has been done on scheduling, however only a few results an optimal schedule. Thus are schedule is made manually. The most frequently used algorithm for scheduling problem is genetic algorithm, but in this research we used Symbiotic Organisms Search Algorithm. This algorithm is used to simulate the behavior of organisms in their environment because of their dependence on the survival of the other species. We tested the algorithm for scheduling laboratory activities and after a number of trials, we concluded that this algorithm is able to provide an optimal solution for scheduling problem with 87.17% accuracy.\",\"PeriodicalId\":351075,\"journal\":{\"name\":\"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAIPT.2017.8320698\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 4th International Conference on Computer Applications and Information Processing Technology (CAIPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAIPT.2017.8320698","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

关于调度的研究已经做了很多,但是得出最优调度的研究很少。因此,时间表是手动制定的。目前最常用的调度算法是遗传算法,但在本研究中我们使用了共生生物搜索算法。该算法用于模拟生物体在其环境中的行为,因为它们依赖于其他物种的生存。我们对该算法进行了实验室活动调度测试,经过多次试验,我们得出结论,该算法能够提供调度问题的最优解,准确率为87.17%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Symbiotic organisms search algorithm for scheduling laboratory sessions in University
Numerous research has been done on scheduling, however only a few results an optimal schedule. Thus are schedule is made manually. The most frequently used algorithm for scheduling problem is genetic algorithm, but in this research we used Symbiotic Organisms Search Algorithm. This algorithm is used to simulate the behavior of organisms in their environment because of their dependence on the survival of the other species. We tested the algorithm for scheduling laboratory activities and after a number of trials, we concluded that this algorithm is able to provide an optimal solution for scheduling problem with 87.17% accuracy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Implementation of real-time static hand gesture recognition using artificial neural network Application of baby's nutrition status using Macromedia Flash Analysis of radio based train control system using LTE-R and analysis of security requirements: The security of the radio based train control system A study on the effective interaction method to improve the presence in social virtual reality game Expert system to optimize the best goat selection using topsis: Decision support system
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1