SOMA
Self-Organizing Migrating Algorithm

Previous special sections:​
CEC2019

GECCO 2019 Special Session on Swarm Intelligence Algorithms: Foundations, Perspectives and Challenges,
​July 8th-12th 2020
Organized by Ivan Zelinka (ivan.zelinka(at)vsb.cz), Swagatam Das, Ponnuthurai Nagaratnam Suganthan and Roman Šenkeřík 

Workshop Papers  https://gecco-2020.sigevo.org/index.html/Workshops for 
SWINGA — Swarm Intelligence Algorithms: Foundations, Perspectives and Challenges
Submission opening: February 27, 2020
Submission deadline: April 3, 2020
Notification: April 17, 2020
Camera-ready: April 24, 2020

For detail please contact us or refer to  https://gecco-2020.sigevo.org/index.html/Important+Dates

Scope and Topics
Evolutionary computation, as well as complex systems dynamics and structure, is a vibrant area of research since the last few decades. To date, a large set of modern and novel techniques are created and used. Such algorithms, systems and their mutual fusion form an inevitable part of computational science and engineering. Most notable examples include not only algorithms inspired by behaviour from biological realm but also chaos control and synchronization, chaotic dynamics for pseudo-random number generators in evolutionary algorithms, use of chaos game with evolutionary algorithms and use of evolution in complex systems design and analysis. 
This special session is concerned about the swarm intelligence algorithm, as the prominent algorithms like Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Firefly, and so on. Also new promising algorithms like Self-Organizing Migrating Algorithm (SOMA), based on competitive-cooperative phases, inherent self-adaptation of movement over the search space, as well as by discrete perturbation mimicking the mutation process known from the classical evolutionary computing techniques will be included. Those algorithms perform well and outperform significantly many classical ones well in both continuous as well as discrete domains. The swarm algorithms have been used successfully on various tasks as the real-time plasma reactor control, aircraft wings optimization, chaos control, large scale, combinatorial and permutative optimisation tasks.
This special session is concern about original research papers discussing new results, as well as its novel improvements tested on widely accepted benchmark tests. This session aims to bring together people from fundamental research, experts from various applications to develop mutual intersections and fusion. Also, a discussion of possible hybridization amongst them as well as real-life experiences with computer applications will be carried out to define new open problems in this interesting and fast-growing field of research. The special session will focus on, but not limited to, the following topics:​

The theoretical aspect of the swarm intelligence 
Swarm intelligence hybridisation with other metaheuristics
The performance improvement, testing and efficiency of the swarm intelligence
Swarm intelligence for complex optimisation scenarios: 
- constrained optimisation
- multiobjective optimisation
- manyobjective optimisation
- multimodal optimisation and niching
- expensive and surrogate assisted optimisation
- dynamic and uncertain optimisation
- large-scale optimisation
Swarm intelligence and its parallelisation
Swarm intelligence for discrete optimisation
Randomness, chaos and its impact on the swarm intelligence dynamics and algorithm performance. 
Swarm intelligence in real-world applications
And more…


You are also welcome to our tutorial  Swarm Intelligence in Cybersecurity

​​For details please contact us or refer to  https://gecco-2020.sigevo.org/