Uncovering Communication Density In PSO Using Complex Network

Pluháček, Michal; Šenkeřík, Roman; Viktorin, Adam; Kadavý, Tomáš

doi:10.7148/2017-0306

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…To capture the density of communication (Pluhacek et al 2017a), the nodes in the network represent the particles in different time points (Particle ID with iteration code). This means that the theoretical maximal number of nodes in the network is the number of particles times the number of iterations.…”

Section: Visualizations For Psomentioning

confidence: 99%

A Review On The Simulation of Social Networks Inside Heuristic Algorithms

Šenkeřík¹,

Pluháček²,

Viktorin³

et al. 2018

ECMS 2018 Proceedings Edited by Lars Nolle, Alexandra Burger, Christoph Tholen, Jens Werner, Jens Wellhausen

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This paper represents a comprehensive review of selected methods for visualization of the population dynamics of the swarm and evolutionary algorithms in the form of networks. The whole idea is based on the obvious similarity between interactions between individuals in a swarm and evolutionary algorithms and for example, users of social networks, society, etc. The analogy between individuals from the population used in an arbitrary evolutionary or swarm-based algorithm and vertices (nodes) of a network is discussed here, as well as between edges in a network and communication between individuals in a population. Simple experiments with four well-known heuristic algorithms are described here, giving an insight into different approaches to the building of the network during metaheuristic run.

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Section: Visualizations For Psomentioning

confidence: 99%

A Review On The Simulation of Social Networks Inside Heuristic Algorithms

Šenkeřík¹,

Pluháček²,

Viktorin³

et al. 2018

ECMS 2018 Proceedings Edited by Lars Nolle, Alexandra Burger, Christoph Tholen, Jens Werner, Jens Wellhausen

Self Cite

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On Relation Between Swarm and Evolutionary Dynamics and Complex Networks

Zelinka

Šenkeřík

2019

Evolution, Development and Complexity

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A Brief Overview of the Synergy Between Metaheuristics and Unconventional Dynamics

Šenkeřík

2019

Lecture Notes in Electrical Engineering

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This brief review paper focuses on the modern and original hybridization of the unconventional dynamics and the metaheuristic optimization algorithms. It discusses the concept of chaos-based optimization in general, i.e. the influence of chaotic sequences on the population diversity as well as at the metaheuristics performance. Further, the non-random processes used in evolutionary algorithms, and finally also the examples of the evolving complex network dynamics as the unconventional tool for the visualization and analysis of the population in popular optimization metaheuristics. This work should inspire the researchers for applying such methods and take advantage of possible performance improvements for the optimization tasks.

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Uncovering Communication Density In PSO Using Complex Network

Cited by 3 publications

References 10 publications

A Review On The Simulation of Social Networks Inside Heuristic Algorithms

A Review On The Simulation of Social Networks Inside Heuristic Algorithms

On Relation Between Swarm and Evolutionary Dynamics and Complex Networks

A Brief Overview of the Synergy Between Metaheuristics and Unconventional Dynamics

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