2019 IEEE Symposium Series on Computational Intelligence


IEEE Symposium Series on Computational Intelligence

December 6-9, 2019 Xiamen, China

 

IEEE Symposium on Cooperative Metaheuristics (IEEE SCM)

Cooperative Metaheuristics refer to the area of having multiple metaheuristic algorithms cooperating with each other to solve an optimization problem. Cooperation could be classified as implicit or explicit. In implicit decomposition, multiple instances implicitly tackle different areas of the search space using various initialization, control parameter settings, etc. In explicit decomposition, each instance operates in a dedicated subspace either by dividing the entire search space among instances or dividing the problem variables (i.e., cooperative coevolution). Many cooperative search algorithms have produced remarkably effective solutions to continuous, discrete, combinatorial, and multi-objective problems in many fields.

Topics

This symposium aims at presenting the latest developments of cooperative metaheuristics techniques, exchanging new ideas and discussing open research questions and future directions. Original contributions that provide novel theories, frameworks, and applications to this topic are very welcome. Potential topics include, but are not limited to:

  • Theoretical analysis (modeling, stability, convergence, etc.) of cooperative or competitive algorithms.
  • Comparative analysis and performance studies of different various cooperative models.
  • Control, tuning, and adaptation strategies of cooperative or competitive algorithms.
  • Parallelized/Hardware implementations (clusters, GPUs, etc.) of cooperative algorithms.
  • Novel cooperative metaheuristic techniques (framework, ensembles, surrogateassisted, problem decomposition, information exchange, etc.).
  • Hybrid cooperative or competitive algorithms.
  • Different types of optimization problems: constrained and unconstrained, single, multi - and many-objective, continuous and discrete optimization, mixed type decision variables, dynamic optimization, and large-scale optimization.
  • Real-world applications.

Symposium Chairs

Mohammed El-Abd

Electrical and Computer Engineering Department, College of Arts and Sciences, American University of Kuwait

Email: melabd@auk.edu.kw

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Shahryar Rahnamayan

Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, Oshawa, Canada

Email: shahryar.rahnamayan@uoit.ca

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Junfeng Chen

College of IOT Engineering, Hohai University, Changzhou, China

Email: chen-1997@163.com

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Shi Cheng

School of Computer Science, Shaanxi Normal University, Xi’an, China

Email: cheng@snnu.edu.cn

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