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2020-11-12 09:38:58
2020-11-12
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theme
in the era of big data and internet of things (iot), optimization problems in research domains and engineering are becoming more and more complicated with properties like thousands of variables and high computational burden. encountering such difficult optimization problems, traditional evolutionary computation techniques executed in sequential would not afford satisfactory solutions in acceptable time. in this situation, distributed and parallel evolutionary computation techniques are critically important for responding fast to these optimization tasks in various areas. even distributed evolutionary computation methods could make it possible to response to online or real-time optimization tasks, such as intelligent transportation scheduling.
this special session aims to demonstrate how distributed evolutionary computation techniques have contributed, and are contributing to the advancement of evolutionary computation research. it prefers a large scope of submissions, which develop and adopt distributed evolutionary computation techniques to tackle optimization tasks in various areas. in addition, the researchers can exchange their innovative ideas on distributed evolutionary computation techniques by submitting manuscripts to this special session.
scope
since complex optimization problems exist in various research domains and engineering areas, all papers that develop and employ distributed evolutionary computation techniques are welcomed. the scope of the special session includes, but is not limited to the following topics:
distributed evolutionary computation algorithms
distributed swarm intelligence and agent-based systems
theoretical basis of distributed evolutionary algorithms
highly scalable distributed evolutionary computation techniques
cloud-based evolutionary computation techniques
gpu-based evolutionary computation techniques
distributed evolutionary big data optimization
applications of distributed evolutionary computation algorithms
mobile evolutionary computation techniques
submission guideline
please follow the submission guideline from the to submit your paper. special session papers are all treated the same as regular conference papers. when sumbmitting your paper, please specify that your paper is for the special session on distributed and parallel evolutionary computation for large-scale global optimization. all papers accepted and presented at cec 2021 will be included in the conference proceedings published by ieee explore, which are typically indexed by ei.
important dates
31 jan 2021: paper submission deadline
22 mar 2021: paper acceptance notification
7 apr 2021: final paper submission & early registration deadline
28 june 2021 - 1 july 2021: conference date
organizer
dr. qiang yang ()
nanjing university of information science and technology, china
qiang yang received his m. s. degree and ph. d. degree from sun yat-sen university, guangzhou, china, in 2014 and 2019, respectively. currently, he is a professor with the school of artificial intelligence, nanjing university of information science and technology, nanjing, china. his current research interests include evolutionary computation algorithms and their applications on real-world problems. so far, he specifically works on large scale optimization algorithms, multimodal optimization algorithms, distributed evolutionary algorithms and their applications on real-world problems, like intelligent transportation, logistics scheduling optimization and smart weather.
prof. wei-neng chen ()
south china university of technology, china.
wei-neng chen received the bachelor’s and ph.d. degrees in computer science from sun yat-sen university, guangzhou, china, in 2006 and 2012, respectively. since 2016, he has been a full professor with the school of computer science and engineering, south china university of technology, guangzhou. he has co-authored over 100 international journal and conference papers, including more than 50 papers published in the ieee transactions journals. his current research interests include computational intelligence, swarm intelligence, network science, and their applications.
dr. chen was a recipient of the ieee computational intelligence society (cis) outstanding dissertation award in 2016, and the national science fund for excellent young scholars in 2016. he is currently the vice-chair of the ieee guangzhou section. he is also a committee member of the ieee cis emerging topics task force. he serves as an associate editor for the ieee transactions on neural networks and learning systems, and the complex & intelligent systems.
prof. zhi-hui zhan ()
south china university of technology, china.
zhi-hui zhan received the bachelor’s and ph.d. degrees in computer science from sun yat-sen university, guangzhou, china, in 2007 and 2013, respectively. he is currently the changjiang scholar young professor with the school of computer science and engineering, south china university of technology, guangzhou. his current research interests include evolutionary computation algorithms, swarm intelligence algorithms, and their applications in real-world problems, and in environments of cloud computing and big data.
dr. zhan was a recipient of the outstanding youth science foundation from national natural science foundations of china in 2018 and the wu wen-jun artificial intelligence excellent youth from the chinese association for artificial intelligence in 2017. his doctoral dissertation was awarded the ieee computational intelligence society outstanding ph.d. dissertation and the china computer federation outstanding ph.d. dissertation. he is listed as one of the most cited chinese researchers in computer science. he is currently an associate editor of the ieee transactions on evolutionary computation, the neurocomputing, and the international journal of swarm intelligence research.
