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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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
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Abstract 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.
AbstractList 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.
Author Karpenko, A.P.
Seliverstov, E.Y.
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Cites_doi 10.22201/icat.16656423.2009.7.03.489
10.1109/CEC.2009.4983227
10.1145/1389095.1389103
10.1145/79173.79181
10.1145/280277.280278
10.5019/j.ijcir.2008.133
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Keywords parallel algorithms
metaheuristic
particle swarm optimization
optimization
evolutionary algorithms
parametric optimization
Language English
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References Bäck (bib0003) 1996
Winter, Greiner, Galvan (bib0006) 2005
Culler, Karp, Patterson, Sahay, Schauser, Santos (bib0009) 1993
Izzo D, Rucinski M, Ampatzis C. Parallel global optimisation meta-heuristics using an asynchronous island-model. In: Evolutionary Computation, 2009. CEC’09. IEEE Congress on. IEEE; 2009, p. 2301–8.
Laguna-Sánchez, Olguín-Carbajal, Cruz-Cortés, Barrón-Fernández, Álvarez-Cedillo (bib00014) 2009; 7
Jordan J, Helwig S, Wanka R. Social interaction in particle swarm optimization, the ranked FIPS, and adaptive multi-swarms. In: GECCO’08: Proceedings of the 10th annual conference on Genetic and evolutionary computation. New York, NY, USA: ACM. ISBN 978-1-60558-130-9; 2008, p. 49–56. URL
Belal, El-Ghazawi (bib0004) 2004; 1
.
Fogel DB. Evolving artificial intelligence. Ph.D. thesis; University of California at San Diego; 1992.
El-Abd M. Cooperative models of particle swarm optimizers. Ph.D. thesis; University of Waterloo; 2008.
Skillicorn, Talia (bib0007) 1998; 30
Rechenberg I. Evolutionsstrategie: Optimierung technischer systeme nach prinzipien der biologischen evolution. frommann-holzbog, stuttgart, 1973. Step-Size Adaptation Based on Non-Local Use of Selection Information In Parallel Problem Solving from Nature (PPSN3) 1994;.
Cantú-Paz (bib0005) 1998; 10
De Jong (bib0002) 2006
Kennedy, Eberhart (bib0001) 2006
Valiant (bib0008) 1990; 33
Wang X, et al. Hybrid nature-inspired computation methods for optimization. Ph.D. thesis; Helsinki University of Technology; 2009.
Skillicorn (10.1016/j.procs.2019.02.075_bib0007) 1998; 30
Winter (10.1016/j.procs.2019.02.075_bib0006) 2005
Belal (10.1016/j.procs.2019.02.075_bib0004) 2004; 1
Cantú-Paz (10.1016/j.procs.2019.02.075_bib0005) 1998; 10
Laguna-Sánchez (10.1016/j.procs.2019.02.075_bib00014) 2009; 7
Kennedy (10.1016/j.procs.2019.02.075_bib0001) 2006
10.1016/j.procs.2019.02.075_bib00011
10.1016/j.procs.2019.02.075_bib00010
Valiant (10.1016/j.procs.2019.02.075_bib0008) 1990; 33
10.1016/j.procs.2019.02.075_bib00015
10.1016/j.procs.2019.02.075_bib00013
Bäck (10.1016/j.procs.2019.02.075_bib0003) 1996
10.1016/j.procs.2019.02.075_bib00012
10.1016/j.procs.2019.02.075_bib00016
De Jong (10.1016/j.procs.2019.02.075_bib0002) 2006
Culler (10.1016/j.procs.2019.02.075_bib0009) 1993
References_xml – volume: 7
  start-page: 292
  year: 2009
  end-page: 309
  ident: bib00014
  article-title: Comparative study of parallel variants for a particle swarm optimization algorithm implemented on a multithreading GPU
  publication-title: Journal of Applied Research Technology
– year: 2006
  ident: bib0002
  publication-title: Evolutionary computation: a unified approach
– reference: Izzo D, Rucinski M, Ampatzis C. Parallel global optimisation meta-heuristics using an asynchronous island-model. In: Evolutionary Computation, 2009. CEC’09. IEEE Congress on. IEEE; 2009, p. 2301–8.
– year: 1996
  ident: bib0003
  publication-title: Evolutionary algorithms in theory and practice
– reference: Fogel DB. Evolving artificial intelligence. Ph.D. thesis; University of California at San Diego; 1992.
– volume: 1
  start-page: 100
  year: 2004
  end-page: 111
  ident: bib0004
  article-title: Parallel models for particle swarm optimizers
  publication-title: IJICIS
– reference: .
– year: 2006
  ident: bib0001
  publication-title: Swarm intelligence
– volume: 10
  start-page: 141
  year: 1998
  end-page: 171
  ident: bib0005
  article-title: A survey of parallel genetic algorithms
  publication-title: Calculateurs paralleles, reseaux et systems repartis
– volume: 30
  start-page: 123
  year: 1998
  end-page: 169
  ident: bib0007
  article-title: Models and languages for parallel computation
  publication-title: ACM Comput Surv
– reference: El-Abd M. Cooperative models of particle swarm optimizers. Ph.D. thesis; University of Waterloo; 2008.
– start-page: 1
  year: 1993
  end-page: 12
  ident: bib0009
  article-title: Logp: Towards a realistic model of parallel computation
  publication-title: ACM Sigplan Notices
– reference: Rechenberg I. Evolutionsstrategie: Optimierung technischer systeme nach prinzipien der biologischen evolution. frommann-holzbog, stuttgart, 1973. Step-Size Adaptation Based on Non-Local Use of Selection Information In Parallel Problem Solving from Nature (PPSN3) 1994;.
– volume: 33
  start-page: 103
  year: 1990
  end-page: 111
  ident: bib0008
  article-title: A bridging model for parallel computation
  publication-title: Commun ACM
– reference: Jordan J, Helwig S, Wanka R. Social interaction in particle swarm optimization, the ranked FIPS, and adaptive multi-swarms. In: GECCO’08: Proceedings of the 10th annual conference on Genetic and evolutionary computation. New York, NY, USA: ACM. ISBN 978-1-60558-130-9; 2008, p. 49–56. URL:
– year: 2005
  ident: bib0006
  article-title: Parallel evolutionary computation
  publication-title: Tech. Rep.
– reference: Wang X, et al. Hybrid nature-inspired computation methods for optimization. Ph.D. thesis; Helsinki University of Technology; 2009.
– volume: 1
  start-page: 100
  year: 2004
  ident: 10.1016/j.procs.2019.02.075_bib0004
  article-title: Parallel models for particle swarm optimizers
  publication-title: IJICIS
– start-page: 1
  year: 1993
  ident: 10.1016/j.procs.2019.02.075_bib0009
  article-title: Logp: Towards a realistic model of parallel computation
– volume: 7
  start-page: 292
  issue: 3
  year: 2009
  ident: 10.1016/j.procs.2019.02.075_bib00014
  article-title: Comparative study of parallel variants for a particle swarm optimization algorithm implemented on a multithreading GPU
  publication-title: Journal of Applied Research Technology
  doi: 10.22201/icat.16656423.2009.7.03.489
– volume: 10
  start-page: 141
  issue: 2
  year: 1998
  ident: 10.1016/j.procs.2019.02.075_bib0005
  article-title: A survey of parallel genetic algorithms
  publication-title: Calculateurs paralleles, reseaux et systems repartis
– year: 2006
  ident: 10.1016/j.procs.2019.02.075_bib0002
– ident: 10.1016/j.procs.2019.02.075_bib00015
  doi: 10.1109/CEC.2009.4983227
– ident: 10.1016/j.procs.2019.02.075_bib00016
  doi: 10.1145/1389095.1389103
– year: 1996
  ident: 10.1016/j.procs.2019.02.075_bib0003
– ident: 10.1016/j.procs.2019.02.075_bib00010
– ident: 10.1016/j.procs.2019.02.075_bib00011
– volume: 33
  start-page: 103
  year: 1990
  ident: 10.1016/j.procs.2019.02.075_bib0008
  article-title: A bridging model for parallel computation
  publication-title: Commun ACM
  doi: 10.1145/79173.79181
– year: 2005
  ident: 10.1016/j.procs.2019.02.075_bib0006
  article-title: Parallel evolutionary computation
– ident: 10.1016/j.procs.2019.02.075_bib00013
– year: 2006
  ident: 10.1016/j.procs.2019.02.075_bib0001
– volume: 30
  start-page: 123
  issue: 2
  year: 1998
  ident: 10.1016/j.procs.2019.02.075_bib0007
  article-title: Models and languages for parallel computation
  publication-title: ACM Comput Surv
  doi: 10.1145/280277.280278
– ident: 10.1016/j.procs.2019.02.075_bib00012
  doi: 10.5019/j.ijcir.2008.133
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SubjectTerms evolutionary algorithms
metaheuristic
optimization
parallel algorithms
parametric optimization
particle swarm optimization
Title Hierarchical Model of Parallel Metaheuristic Optimization Algorithms
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