CEC2021 SS-38: Analysis of Dynamics of Evolutionary Computation and Its Applications

Scopes and Aims:

   Evolutionary computation has shown very high performance in multi-objective optimization and has achieved a lot of results. Especially in recent researches related to artificial intelligence, multi-objective optimization techniques are indispensable. However, evolutionary computation, which performs multi-point search by sequential computation, requires a huge number of function evaluations and a huge amount of computational resources.

In order to overcome these problems, it is necessary to develop efficient algorithms or to implement a very high performance computing environment.

   In order to develop efficient algorithms, it is important to analyze the global optimum solution-seeking dynamics of evolutionary computation and to design algorithms based on the analysis results. In addition, analysis of the solution seeking dynamics of evolutionary algorithms is also essential for the implementation of high-performance computing environments.

    In this special session, we will discuss the global optimum solution-seeking dynamics of various evolutionary computation algorithms, novel algorithms based on the analysis results, implementations of massively parallel evolutionary algorithms using cloud computing systems and services, and distributed implementations of multipurpose evolutionary algorithms.

This special session welcomes results on any "efficient" evolutionary computation, including the following topics

Topics of interest include but are not limited to:

- Analysis of evolutionary computation

- Analysis of swarm intelligence

- Single objective evolutionary computation

- Muti/Many objective evolutionary computation

- Evolutionary computation for machine learning

- Parallel and distributed multi/many objective evolutionary algorithms

- Parallel and distributed Swarm Intelligence

- Implementation of massively parallel evolutionary computation in cloud computing systems and/or services

- Implementation of distributed evolutionary computation on many-core architecture such as GPUs

- Applications of parallel and evolutionary computation techniques in the smart city

Organizers (Contact information):

Kenya Jin’no (kjinno@tcu.ac.jp)

Yuji Sato (yuji@k.hosei.ac.jp)

Noriyuki Fujimoto (fujimoto@cs.osakafu-u.ac.jp)

Toshimichi Saito  (tsaito@hosei.ac.jp)