Hierarchical Model of Parallel Metaheuristic Optimization Algorithms

The paper introduces a novel model of parallel metaheuristic optimization algorithms. The hierarchical graph model of a parallel optimization algorithm is proposed. It consists of the model for a parallel optimization algorithm at the top level of the hierarchy and the model for a sequential optimiz...

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Bibliographic Details
Published in:Procedia computer science Vol. 150; pp. 441 - 449
Main Authors: Seliverstov, E.Y., Karpenko, A.P.
Format: Journal Article
Language:English
Published: Elsevier B.V 2019
Subjects:
evolutionary algorithms
metaheuristic
optimization
parallel algorithms
parametric optimization
particle swarm optimization
parallel algorithms
metaheuristic
particle swarm optimization
optimization
evolutionary algorithms
parametric optimization
ISSN:1877-0509, 1877-0509
Online Access:Get full text
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Summary:The paper introduces a novel model of parallel metaheuristic optimization algorithms. The hierarchical graph model of a parallel optimization algorithm is proposed. It consists of the model for a parallel optimization algorithm at the top level of the hierarchy and the model for a sequential optimization algorithm at the bottom level. The unified representation of a metaheuristic optimization algorithm, which allows representing a class of metaheuristic algorithms, is used. The extension of the proposed model to the parametric hierarchical model is proposed. Graph model transformations for a parallel algorithm analysis and synthesis are introduced. The representation of several metaheuristic algorithms with the proposed model is discussed.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2019.02.075