Quantum particle swarm optimization for multiobjective combined economic emission dispatch problem using cubic criterion function

Fahad Parvez Mahdi, P. Vasant, M. Rahman, M. Abdullah-Al-Wadud, J. Watada, V. Kallimani
{"title":"Quantum particle swarm optimization for multiobjective combined economic emission dispatch problem using cubic criterion function","authors":"Fahad Parvez Mahdi, P. Vasant, M. Rahman, M. Abdullah-Al-Wadud, J. Watada, V. Kallimani","doi":"10.1109/ICIVPR.2017.7890879","DOIUrl":null,"url":null,"abstract":"In this research, quantum particle swarm optimization (QPSO) is utilized to solve multiobjective combined economic emission dispatch (CEED) problem formulated using cubic criterion function considering a uni wise max/max price penalty factor. QPSO is implemented on a 6-unit power generation system and compared with Lagrangian relaxation, particle swarm optimization (PSO) and simulated annealing (SA). The obtained results verified the effectiveness and demonstrate the robustness of QPSO method. This research suggests that QPSO can be used as an effective and robust tool in other power dispatch problems.","PeriodicalId":126745,"journal":{"name":"2017 IEEE International Conference on Imaging, Vision & Pattern Recognition (icIVPR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Imaging, Vision & Pattern Recognition (icIVPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIVPR.2017.7890879","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

Abstract

In this research, quantum particle swarm optimization (QPSO) is utilized to solve multiobjective combined economic emission dispatch (CEED) problem formulated using cubic criterion function considering a uni wise max/max price penalty factor. QPSO is implemented on a 6-unit power generation system and compared with Lagrangian relaxation, particle swarm optimization (PSO) and simulated annealing (SA). The obtained results verified the effectiveness and demonstrate the robustness of QPSO method. This research suggests that QPSO can be used as an effective and robust tool in other power dispatch problems.
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
基于三次准则函数的多目标组合经济排放调度问题的量子粒子群优化
本文采用量子粒子群算法求解考虑单最大/最大价格惩罚因子的三次准则函数多目标联合经济排放调度问题。在6台发电系统上实现了量子粒子群优化算法,并与拉格朗日弛豫、粒子群优化和模拟退火算法进行了比较。得到的结果验证了QPSO方法的有效性和鲁棒性。这一研究表明,量子粒子群算法可以作为一种有效的鲁棒工具用于解决其他电力调度问题。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Smart material interfaces: Playful and artistic applications Detection of Interstitial Lung Disease using correlation and regression methods on texture measure Single cell mass measurement from deformation of nanofork Handwritten Arabic numeral recognition using deep learning neural networks Chord Angle Deviation using Tangent (CADT), an efficient and robust contour-based corner detector
×
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