Special Session on Theoretical Foundations of Bio-inspired Computation

Bio-inspired computing techniques have been shown to be powerful approximation solvers for sophisticated optimization problems in practice. During the past two decades, there are also a lot of efforts on theoretical analysis of these techniques, particularly on analyzing their running time complexity until finding an optimal or approximate solution of a given optimization problem. The theoretical results can help practitioners better understand the working principles of bio-inspired computing techniques, and thus, design efficient algorithms. However, compared with the great success in practice, the theoretical foundation of bio-inspired computing techniques is still underdeveloped.

The primary aim of this special session is to bring together researchers working on theoretical analysis of bio-inspired computing techniques, and to provide a forum for them to discuss the latest outcomes and new directions.


The original contributions in the theory of bio-inspired computation are welcome. Topics of interest include, but are not limited to:

  • General analytical methods like drift analysis
  • Exact and approximation runtime analysis
  • Parameterized complexity analysis
  • Black box complexity
  • Dynamic and static parameter choices
  • Population diversity
  • Population dynamics
  • Fitness landscape and problem difficulty analysis
  • All problem domains will be considered including:
    • combinatorial and continuous optimization
    • single-objective and multi-objective optimization
    • constrained optimization
    • dynamic and stochastic optimization
    • co-evolution and evolutionary learning

In addition to rigorous mathematical investigations, carefully crafted experimental studies contributing towards the theoretical foundations of bio-inspired computation are also welcome.

Important Dates

  • Submission deadline: January 31, 2022
  • Notification: April 26, 2022
  • Final paper submission: May 23, 2022


Aneta Neumann (aneta.neumann@adelaide.edu.au)
University of Adelaide, Australia

Chao Qian (qianc@nju.edu.cn)
Nanjing University, China

Per Kristian Lehre (P.K.Lehre@cs.bham.ac.uk)
University of Birmingham, U.K.

*Supported by IEEE CIS Task Force on Theoretical Foundations of Bio-inspired Computation