IEEE CEC 2018 Special Session
at Rio de Janeiro, Brazil
( www.ecomp.poli.br/~wcci2018/ )

Parallel and Distributed Evolutionary Computation in the Inter-Cloud Era (PDEC)

Recent advances in cloud computing lead to a global infrastructure of "the Inter-cloud" (clouds of cloud systems) that can be utilized through the Internet to provide with virtually infinite IT resources such as virtual machines and storage units just by calling web-service APIs through the Internet.

It is necessary to have enough resources and complexities in the environment for the individuals to "evolve". Cloud systems may even offer tens of thousands of virtual machines, terabytes of memories and exabytes of storage capacity. Current trend toward many-core architecture increases the number of cores even more dramatically: we may have more than a million of cores to offer extremely massive parallelization.

In this special session, we will discuss parallel and distributed evolutionary computation in the cloud era such as implementation of massively parallel evolutionary algorithms employing cloud computing systems and services, parallel implementation of evolutionary algorithms on many-core architectures including GPUs, and we also welcome any types of parallel and distributed evolutionary computation on any unconventional types of computing environment in this special session including the following themes.

Scope and Topics:

Topics of interest include, but are not limited to:

  • Implementation of parallel and distributed evolutionary computation in cloud computing systems and/or services
  • Implementation of massively parallel evolutionary computation on many-core architecture such as GPUs
  • Parallel and distributed evolutionary multi/many objective optimization
  • Large-scale multi-objective optimization in cloud computing systems
  • Parallel and distributed Swarm Intelligence
  • Parallel and distributed evolutionary machine learning techniques
  • Design and theory of scalable evolutionary algorithms
  • Development of parallel and distributed evolutionary computation framework in cloud computing systems
  • Applications of parallel and evolutionary computation techniques in cloud or other modern computing environment
  • Applications of EC and other bio-inspired paradigms to peer to peer systems, and distributed EC algorithms that use them.
  • Peer-to-peer computing, volunteer computing and zero-cost distributed computing. Large scale autonomous systems, sneaky or parasite computing using the browser or other widely available infrastructure. Internet of Things or Everything (IoT or IoE).

Important Dates:

Paper submission February 1st, 2018 (Postponed)
Notification of acceptance March 15, 2018
Final paper submission May 1st, 2018
Conference dates July 8-13, 2018

Paper Submission:

Manuscripts should be prepared according to the standard format and page limit of regular papers specified in CEC 2018 webpage ( www.ecomp.poli.br/~wcci2018/submissions/#guidelines ), and submitted via the official submission system.

Special session papers are treated the same way as regular conference papers. Please specify that your paper is for the special session on PDEC: Parallel and Distributed Evolutionary Computation in the Inter-Cloud Era. All accepted papers will be published in the CEC electronic proceedings and included in the IEEE Xplore digital library, and indexed by EI Compendex.

PC Members:

  • Juan Julián Merelo Guervós, University of Granada jjmerelo@gmail.com
  • Minami Miyakawa, Hosei University miyakawa@cis.k.hosei.ac.jp
  • Yoshiyuki Matsumura, Shinshu University matsumu@shinshu-u.ac.jp
  • Masaharu Munetomo, Hokkaido University munetomo@iic.hokudai.ac.jp
  • Kazuhiro Ohkura, Hiroshima University kohkura@hiroshima-u.ac.jp
  • Antonio López Jaimes, Metropolitan Autonomous University tonio.jaimes@gmail.com
  • Keiko Ono, Ryukoku University kono@rins.ryukoku.ac.jp
  • Akira Oyama, JAXA oyama@flab.isas.jaxa.jp
  • Mikiko Sato, Tokai University mikiko.sato@tokai.ac.jp
  • Shiqin Yang, Shanghai Ocean University worldyangshiqin@gmail.com
  • Tomoaki Tatsukawa, Tokyo University of Science tatsukawa@rs.tus.ac.jp

Contact information:

Yuji Sato, Hosei University, Japan. (yuji@k.hosei.ac.jp)
Noriyuki Fujimoto, Osaka Prefecture University, Japan. (fujimoto@cs.osakafu-u.ac.jp)
Hiroyuki Sato, University of Electro-Communications, Japan. (h.sato@uec.ac.jp)

Organizers:

  • Yuji Sato
    received the B.E and Ph.D. degrees in engineering from the University of Tokyo, Japan in 1981 and 1997, respectively. From 1981 to 2000, he was with Hitachi Ltd., Tokyo, Japan. In April 2000, he joined the Faculty of Computer and Information Sciences at Hosei University, Japan, as an Associate Professor, and became a Professor in April 2001. From 2007 to 2008, he was a visiting scholar at Illinois Genetic Algorithms Laboratory (IlliGAL). His current research areas include evolutionary computation on many-core architecture and evolution of machine learning techniques in design. He received the 2014 Highly Commended Paper Award of IJICC. He is a member of the IEEE Computational Intelligence Society, the IEEE Computer Society, the ACM/SIGEVO, the Japanese Society for Evolutionary Computation, and the Information Processing Society of Japan. He is also a member of program committee of GECCO since 1999.

  • Noriyuki Fujimoto
    received the B.E and Ph.D. degrees in engineering from Osaka University, Japan in 1992 and 2000, respectively. From 1997 to 2002, he was with the Graduate School of Engineering Science at Osaka University, Japan, as a Research Associate. In April 2002 he joined the Graduate School of Information Science and Technology at Osaka University, Japan, as an Associate Professor. In April 2008, he joined the Graduate School of Science at Osaka Prefecture University, Japan, as a Professor. His current research areas include GPU computing and Grid computing. He is a member of the IEEE Computational Intelligence Society, the IEEE Computer Society, the ACM, the Institute of Electronics, Information, and Communication Engineers, and the Information Processing Society of Japan.

  • Hiroyuki Sato
    received M.E. and Ph.D. degrees from Shinshu University in 2005 and 2009, respectively. From 2009 to 2015, he was an assistant professor in the University of Electro-Communications. Currently, he is an Associate Professor in the University of Electro-Communications from 2016. His research interest includes evolutionary multi and many-objective optimization and its applications. He received best paper awards at GECCO2011 and GECCO2014 in EMO track. He organized special sessions on Many-objective optimization at CEC2015 and CEC2016. He presented a special invited talk, "Evolutionary Many-Objective Optimization: Difficulties and Approaches," in the workshop on evolutionary multi-objective optimization at CEC2015.