2019 IEEE CEC Special Session on “Cooperative Evolutionary Computation”

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2019 IEEE Congress on Evolutionary Computation

Special Session on “Cooperative Evolutionary Computation”


Cooperative Evolutionary Computation refers to the area of having multiple evolutionary algorithmic instances 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 domain due to different initialization, parameter settings … etc. In explicit decomposition, each instance operates in a dedicated subdomain either by dividing the entire domain between instances or dividing the problem variables (i.e. cooperative coevolution). Moreover, cooperative algorithms could be classified as homogeneous (multiple instances of the same evolutionary algorithm) or heterogeneous (instances of different evolutionary algorithms). Many cooperative search algorithms have produced remarkably effective solutions, with a faster speed of convergence, to continuous, large-scale, discrete, combinatorial and multi-objective problems in many fields.


This special session aims at presenting the latest developments of cooperative evolutionary computation 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 (mathematical modeling, stability, convergence … etc.) of cooperative evolutionary algorithms.

  • Control, parameter tuning, and adaptation strategies of cooperative evolutionary algorithms.

  • Parallelized/Hardware implementations (clusters, GPUs, FPGAs … etc.) of cooperative evolutionary algorithms.

  • Novel cooperative techniques (frameworks, problem decomposition, information exchange … etc.).

  • Hybrid cooperative evolutionary algorithms.

  • Different types of optimization problems: constrained and unconstrained, single, multi and many-objective, continuous and discrete optimization, mixed decision variables, dynamic optimization, and large-scale optimization.

  • Real-world applications of cooperative evolutionary algorithms.


Please follow the IEEE CEC2019 instruction for authors and submit your paper via the IEEE CEC 2019 online submission system. Please specify that your paper is for the Special Session on "Cooperative Evolutionary Computation".

Important Dates

  • Paper submission: 7 January, 2019

  • Decision notification: 7 March, 2019

  • Camera ready paper due: 31 March, 2019

  • Registration: 31 March, 2019

  • Conference: 10 June, 2019


Mohammed El-Abd, American University of Kuwait, melabd@auk.edu.kw

Junfeng Chen, Hohai University, Changzhou, China, chen-1997@163.com

Shi Cheng, Shaanxi Normal University, Xi’an, China, cheng@snnu.edu.cn

2018-09-26 22:33

Welcome to Swarm Intelligence community

Swarm Intelligence is a field of Computer science. It is a form of Artificial intelligence. Some animals, mostly insects like ants, or bees form large colonies. These colonies are made of many animals that communicate with each other. Each animal is relatively simple, but by working together with other animals it is able to solve complex tasks.


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