CEC 2021 Special Session

Large-scale Multi- and Many-objective Optimization and its Applications

Theme

The field of large-scale multi/many-objective optimization (LSMO) has developed rapidly over the past decade due to increasing demands (e.g., design of high-fidelity products, automatic search of neural architectures, and signal processing) in various areas (e.g., machine learning, network science, software engineering, and economics). Nevertheless, the proposal of real-world test suites, efficient algorithms, and impactful applications for promoting the research in LSMO remains unsatisfactory. First, the ineffectiveness of the genetic operators results in the requirement of a huge number of function evaluations for achieving an acceptable result. Consequently, unbearable time or computing resources are required, leading to the restriction of large-scale multi/many-objective algorithms in real-world applications. Furthermore, the aggravation of the conflict between convergence and diversity, as well as the reliability of benchmark problems, have become key barriers to the design of effective large-scale multi/many-objective algorithms. All of these suggest the pressing need for new methodologies designed for dealing with LSMO problems, new test functions tailored for experimental and comparative studies of large-scale multi/many-objective algorithms.

List of Topics

We welcome high-quality original submissions addressing various topics related to evolutionary large-scale multi/many-objective optimization, but are not limited to:

(1)  Algorithms for large-scale multi/many-objective optimization

New ideas for solving large-scale multi/many-objective optimization, including search operators, mating restriction, and environmental selection.

Effective techniques for large-scale multi/many-objective optimization.

Sparse optimization.

Variable reduction techniques for large-scale multi/many-objective optimization.

Constraint handling techniques for large-scale multi/many-objective optimization.

Computationally expensive large-scale multi/many-objective optimization.

Algorithms for other kinds of large-scale multi/many-objective optimization.

Other benchmark problems for large-scale multi/many-objective optimization.

(2) Benchmark problems for large-scale multi/many-objective optimization

Benchmark problems for large-scale sparse optimization.

Benchmark problems for constrained large-scale multi/many-objective optimization.

Benchmark problems for computationally expensive large-scale multi/many-objective optimization.

Other benchmark problems for large-scale multi/many-objective optimization.

(3) Applications of large-scale multi/many-objective optimization

Automatic machine learning, including hyperparameter optimization, neuroevolution, neural architecture search, neural network training and their applications, etc.

Transportation and logistics, including vehicle routing, facility location and scheduling, etc.

Applications for transforming complex tasks into large-scale multi/many-objective optimization problems.

Applications for other tasks, including feature selection, data clustering, signal reconstruction, software configuration, and portfolio optimization, etc.

Important Dates

  • Paper Submission Deadline: 31 January 2021
  • Paper Acceptance Notification: 22 March 2021
  • Final Paper Submission Deadline: 7 April 2021
  • Early Registration Deadline: 7 April 2021
  • Conference Dates: 28 June 2021 – 1 July 2021

Organizers:

  • Ran Cheng

Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

Email: ranchengcn@gmail.com

Homepage: http://emi.sustech.edu.cn/?p=4665

  • Cheng He

Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

Email: chenghehust@gmail.com

Homepage: http://emi.sustech.edu.cn/?p=5121

  • Xingyi Zhang

School of Computer Science, Anhui University, China

Email: xyzhanghust@gmail.com

Homepage: http://cs.ahu.edu.cn/7d/43/c11201a163139/page.htm

  • Ye Tian

Institutes of Physical Science and Information Technology, Anhui University, China

Email: field910921@gmail.com

Homepage: http://wky.ahu.edu.cn/2020/0420/c13481a233924/page.htm

  • Yaochu Jin

Department of Computer Science, University of Surrey, United Kingdom

Email: yaochu.jin@surrey.ac.uk

Homepage: https://www.surrey.ac.uk/people/yaochu-jin