Neural network with migration parallel ga for adaptive control of integrated DE-PSO parameters

Hieu Pham, Sousuke Tooyama, Hiroshi Hasegawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study develops an evolutionary strategy called DEPSO-GANN, which uses an artificial neural network (ANN) based on a parallel genetic algorithm (PGA) with migration for the adaptive control of integrated differential evolution (DE) and particle swarm optimization (PSO) to solve large-scale optimization problems, reduce calculation costs, and improve the stability of convergence towards the optimal solution. This approach combines the global search ability of DE and the local search ability of adaptive system with migration parallel GA. The proposed algorithm incorporates concepts from DE, PSO, PGA and neural networks (NN) to facilitate the adaptive control of parameters. DEPSO-GANN is applied to several numerical benchmark tests with multiple dimensions to evaluate its performance, it is also compared with other evolutionary algorithms (EAs) and memetic algorithms (MAs), which is shown to be statistically significantly superior to other EAs and MAs. We confirm satisfactory performance through various benchmark tests.

Original languageEnglish
Title of host publicationProceedings - 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages13-18
Number of pages6
ISBN (Print)9780769550732
DOIs
Publication statusPublished - 2015 Jan 8
Event8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013 - Cardiff, Wales, United Kingdom
Duration: 2013 Sep 102013 Sep 13

Other

Other8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013
CountryUnited Kingdom
CityCardiff, Wales
Period13/9/1013/9/13

Fingerprint

Particle swarm optimization (PSO)
Neural networks
Parallel algorithms
Evolutionary algorithms
Genetic algorithms
Adaptive systems
Costs

Keywords

  • Adaptive Plan
  • Differential Evolution
  • Neural Network
  • Parallel Genetic Algorithm
  • Particle Swarm Optimization

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computational Theory and Mathematics
  • Computer Science Applications

Cite this

Pham, H., Tooyama, S., & Hasegawa, H. (2015). Neural network with migration parallel ga for adaptive control of integrated DE-PSO parameters. In Proceedings - 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013 (pp. 13-18). [7004910] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EUROSIM.2013.13

Neural network with migration parallel ga for adaptive control of integrated DE-PSO parameters. / Pham, Hieu; Tooyama, Sousuke; Hasegawa, Hiroshi.

Proceedings - 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013. Institute of Electrical and Electronics Engineers Inc., 2015. p. 13-18 7004910.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Pham, H, Tooyama, S & Hasegawa, H 2015, Neural network with migration parallel ga for adaptive control of integrated DE-PSO parameters. in Proceedings - 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013., 7004910, Institute of Electrical and Electronics Engineers Inc., pp. 13-18, 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013, Cardiff, Wales, United Kingdom, 13/9/10. https://doi.org/10.1109/EUROSIM.2013.13
Pham H, Tooyama S, Hasegawa H. Neural network with migration parallel ga for adaptive control of integrated DE-PSO parameters. In Proceedings - 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013. Institute of Electrical and Electronics Engineers Inc. 2015. p. 13-18. 7004910 https://doi.org/10.1109/EUROSIM.2013.13
Pham, Hieu ; Tooyama, Sousuke ; Hasegawa, Hiroshi. / Neural network with migration parallel ga for adaptive control of integrated DE-PSO parameters. Proceedings - 8th EUROSIM Congress on Modelling and Simulation, EUROSIM 2013. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 13-18
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