Accelerating evolutionary computation using estimated convergence points

Jun Yu, Yan Pei, Hideyuki Takagi

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

3 Citations (Scopus)

Abstract

We use the convergence points estimated by our proposed method as elite individuals for evolutionary computation and evaluate the acceleration effect and analyze the effect and computational cost. The worst individuals in population are replaced with the convergence points estimated from the moving vectors between parent individuals and their offspring; i.e. these convergence points are used as elite individuals. Differential evolution (DE) and 14 benchmark functions are used in our evaluation experiments. The experimental results show that use of the estimated convergence points as elite can accelerate DE search in spite of the calculation cost of the convergence points. We finally analyze the components of the proposed estimation method to improve cost-performance.

Original languageEnglish
Title of host publication2016 IEEE Congress on Evolutionary Computation, CEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1438-1444
Number of pages7
ISBN (Electronic)9781509006229
DOIs
Publication statusPublished - Nov 14 2016
Event2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, Canada
Duration: Jul 24 2016Jul 29 2016

Other

Other2016 IEEE Congress on Evolutionary Computation, CEC 2016
CountryCanada
CityVancouver
Period7/24/167/29/16

Fingerprint

Evolutionary Computation
Evolutionary algorithms
Costs
Differential Evolution
Accelerate
Computational Cost
Benchmark
Experiments
Evaluate
Evaluation
Experimental Results
Experiment

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Modelling and Simulation
  • Computer Science Applications
  • Control and Optimization

Cite this

Yu, J., Pei, Y., & Takagi, H. (2016). Accelerating evolutionary computation using estimated convergence points. In 2016 IEEE Congress on Evolutionary Computation, CEC 2016 (pp. 1438-1444). [7743959] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2016.7743959

Accelerating evolutionary computation using estimated convergence points. / Yu, Jun; Pei, Yan; Takagi, Hideyuki.

2016 IEEE Congress on Evolutionary Computation, CEC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1438-1444 7743959.

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

Yu, J, Pei, Y & Takagi, H 2016, Accelerating evolutionary computation using estimated convergence points. in 2016 IEEE Congress on Evolutionary Computation, CEC 2016., 7743959, Institute of Electrical and Electronics Engineers Inc., pp. 1438-1444, 2016 IEEE Congress on Evolutionary Computation, CEC 2016, Vancouver, Canada, 7/24/16. https://doi.org/10.1109/CEC.2016.7743959
Yu J, Pei Y, Takagi H. Accelerating evolutionary computation using estimated convergence points. In 2016 IEEE Congress on Evolutionary Computation, CEC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1438-1444. 7743959 https://doi.org/10.1109/CEC.2016.7743959
Yu, Jun ; Pei, Yan ; Takagi, Hideyuki. / Accelerating evolutionary computation using estimated convergence points. 2016 IEEE Congress on Evolutionary Computation, CEC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1438-1444
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