Self-Organizing Migrating Algorithm

2019 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION

WELLINGTON, NEW ZEALAND,
10-13th June 2019

CEC 2019

 

 

Special Session on

Self-Organizing Migrating Algorithm:
Foundations, Perspectives and Challenges.
 

Organized by

Ivan Zelinka, Swagatam Das and Ponnuthurai Nagaratnam Suganthan

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Evolutionary computation, as well as complex systems dynamics and structure, is a vibrant area of research since 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 synchronisation, chaotic dynamics for pseudo-random number generators in evolutionary algorithms, use of chaos game with evolutionary algorithms and use evolution in complex systems design and analysis.

This special session is concerned about the Self-Organizing Migrating Algorithm (SOMA) published since 2001 in journals as well as books (somaalgorithm.com) and belonging to the class of swarm intelligence techniques. Compare to other prominent swarm intelligence paradigms as for example particle swarm optimization (PSO), ant colony optimization (ACO), Firefly (FF) SOMA is distinguished by competitive-cooperative phases, inherent self-adaptation of movement over the search space as well as by discrete perturbation mimicking the mutation process known from classical evolutionary techniques. The SOMA perform significantly well in both continuous as well as discrete domains.

The SOMA has been used successfully on various tasks as the real-time plasma reactor control, aircraft wings optimisation, chaos control, large scale, combinatorial and permutative optimization tasks.

This special session is concern about original research papers discussing new results on and with SOMA, as well as its novel improvements tested on widely accepted benchmark tests.

 

Scope and Topics

This session aims to bring together people from fundamental research, experts from various applications of SOMA to develop mutual intersections and fusion. Also, discussion of possible hybridisation 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 SOMA 

• SOMA hybridisation with other metaheuristics

• The performance improvement, testing and efficiency of the SOMA

• SOMA for complex optimisation scenarios: 

  • constraint optimisation

  • multiobjective optimization

  • manyobjective optimization

  • multimodal optimization and niching

  • expensive and surrogate assisted optimization

  • dynamic and uncertain optimization

  • large scale optimization

• SOMA and its parallelisation

• SOMA for discrete optimisation

• Randomness, chaos and its impact on the SOMA dynamics and algorithm performance. 

• SOMA in real-world applications

• SOMA, evolutionary algorithms and complex networks

• And more…