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[转载]CFP | IEEE Transactions on Evolutionary Computation

已有 2101 次阅读 2018-4-27 11:16 |个人分类:科研记事|系统分类:博客资讯|文章来源:转载

 CFP | IEEE Transactions
on Evolutionary Computation


人类社会已经进入了一个智能技术的新时代,机器、信息和人类紧密结合在大规模的网络物理社会空间(CPSS)中。其结果是,大量的大规模问题,如优化和学习,正随着探索和开发物理世界,精神世界和虚拟世界而兴起。随着大数据分析、通信、计算和数据存储的巨大进步,进化计算(EC)作为处理复杂问题的有效方法,将在CPSS中扮演更重要的角色。这可以通过在几个方面的进展来实现,例如开发更强大的大规模优化问题的EC技术,在CPSS中将EC和新兴技术相连接(例如平行系统的理论和方法),从而提供管理和控制复杂系统的新机制,其涉及工程和社会两方面的复杂性问题,并建立能够描述、预测和规定真实世界复杂系统演化的大规模演化系统。这一研究旨在促进EC在上述方面的发展。

 

IEEE Transactions on Evolutionary Computation Special Issue on Parallel Evolution for Large Scale Optimization正在征稿,截稿日期2018年11月1日,欢迎相关领域的专家学者踊跃投稿!


CALL FOR PAPERS


IEEE Transactions on Evolutionary Computation 
Special Issue on Parallel Evolution
for 
Large Scale Optimization

 

I. AIM AND SCOPE

Human societies have entered a new era of intelligent technology, where machines, information, and humans are tightly coupled in the large scale cyber-physical-social spaces (CPSS). As a result, a lot of large-scale problems, such as optimizationand learning, are emerging with the aim to explore and exploit of the physical world, mental world and virtual world. With the dramatic advances in big data analytics, communications, computing and data storage, it is expected that Evolutionary Computation (EC), as a powerful approach to complex problems, would play an even more important role in CPSS. This could be achieved through advances in several aspects, such as developing more powerful EC techniques for large-scale optimization problems, bridging EC and emergent techniques in CPSS (e.g., the theory and methods of parallel systems) to offer new mechanisms for managing and controlling complex systems that involve complexity issues of both engineering and social dimensions, and building large-scale evolution systems that are capable of describing, predicting and prescribing the evolution of real-world complex systems. This special issue aims at promoting the development of EC in the above aspects.

 

II. THEMES

Researchers are encouraged to submit their latest investigations on EC, either fundamental advances or practical cases, for large-scale problems as well as systems to the special issue. In addition to advancements of EC for large-scale optimization, learning and other challenging problems that arise in complex systems, research on building large-scale evolutionary systems for simulation, management and control of cyber-physical-social systems are most welcome as well. Topics of interest include (but are not limited to):


● Evolutionary Computation for Large-Scale Optimization Problems;

● Evolutionary Computation for Large-Scale Learning Problems;

● Evolutionary Computation for Complex Systems;

● Evolutionary Computation for Optimal Management and Control in CPSS;

● Theoretical Analysis on Evolutionary Computation for Large-Scale Problems and Systems;

● Adaptation and Learning Mechanisms for large-scale evolutionary systems;

● Parallel Evolutionary Computation Techniques;

New Implementation Technologies of Evolutionary Computation for Emerging Large-Scale problems;

● New Trends for Evolutionary Computation in Large Scale Optimization.

 

III. SUBMISSION

Manuscripts should be prepared according to the “Information for Authors” section of the journal found at

http://cis.ieee.org/ieee-transactions-on-evolutionary-computation/.

Please submit your manuscript in electronic form through:

http://mc.manuscriptcentral.com/tevc-ieee/,

by selecting “PEforLSO Special Issue Papers” as the Manuscript Type. Also, please indicate “PEforLSO Special Issue Paper” in the comments to the Editor-in-Chief. Submitted papers will be reviewed by at least three different experts. Submission of a manuscript implies that it is the authors’ original unpublished work and is not being submitted for possible publication elsewhere.

 

IV. IMPORTANT DATES

Submission open: May 15, 2018

Submission deadline: November 1, 2018

Tentative publication date: 2019

For further information, please contact one of the following Guest Editors.

 

V. GUEST EDITORS

Fei-Yue Wang (The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, China, and Qingdao Academy of Intelligent Industries, China), with e-mail:

feiyue.wang@ia.ac.cn


Qinglai Wei (The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, China), with e-mail: 

qinglai.wei@ia.ac.cn


Ke Tang (Department of Computer Science and Engineering, Southern University of Science and Technology, China), with e-mail: 

tangk3@sustc.edu.cn


Carlos A. Coello Coello (Department of Computer Science, CINVESTAV-IPN, Mexico), with e-mail:

ccoello@cs.cinvestav.mx

      

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