A Comparative Analysis of Bioinspired Algorithms for Solving the Problem of Optimization of Circulant and Hypercirculant Networks

The solution of the optimization problem of constructing regular networks (graphs) that are optimal over the average diameter is investigated. Two classes of parametrically described regular networks are investigated - circulant and hypercirculant networks. An approach using bioinspired algorithms f...

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Veröffentlicht in:2019 15th International Asian School-Seminar Optimization Problems of Complex Systems (OPCS) S. 100 - 103
Hauptverfasser: Monakhov, Oleg, Monakhova, Emilia
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.08.2019
Schlagworte:
average diameter
bioinspired algorithms
Biological cells
circulant graph
Generators
Genetic algorithms
hypercirculant
network optimization
Optimization
Reliability
Sociology
Statistics
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Zusammenfassung:The solution of the optimization problem of constructing regular networks (graphs) that are optimal over the average diameter is investigated. Two classes of parametrically described regular networks are investigated - circulant and hypercirculant networks. An approach using bioinspired algorithms for the automatic synthesis of parametric descriptions of optimal circulant and hypercirculant networks has been developed. A comparative analysis of five different bioinspired algorithms (genetic algorithm, differential evolution, particle swarm optimization, algorithm of artificial bee colony and firefly algorithm) was carried out using them to solve this optimization problem. For the found optimal networks structural characteristics such as diameter, average diameter, bandwidth, reliability were obtained, and these networks were compared according to these characteristics.
DOI:10.1109/OPCS.2019.8880247