Differential evolution using jumping genes adaptation

Ashish M. Gujarathi*, Saumitra Purohit, Rohan Manchanda, Debabrata Ghosh

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

Jumping gene adaptation of differential evolution algorithm (DE-JGa) is proposed in this study. Detailed working principle of proposed algorithm is given. The performance of the proposed algorithm (DE-JGa) is compared with the performance of existing algorithms (differential evolution (DE) and modified differential evolution (MDE)] by applying these algorithms to some selected benchmark test problems. Thorough algorithm specific study is carried out to check the robustness of individual algorithms with respect to its control parameters, such as crossover constant (CR), number of population points (NP), scaling factor (F) and the number of generations.

Original languageEnglish
Title of host publicationProceedings of the 5th Indian International Conference on Artificial Intelligence, IICAI 2011
Pages353-370
Number of pages18
Publication statusPublished - 2011
Externally publishedYes
Event5th Indian International Conference on Artificial Intelligence, IICAI 2011 - Tumkur, India
Duration: Dec 14 2011Dec 16 2011

Publication series

NameProceedings of the 5th Indian International Conference on Artificial Intelligence, IICAI 2011

Other

Other5th Indian International Conference on Artificial Intelligence, IICAI 2011
Country/TerritoryIndia
CityTumkur
Period12/14/1112/16/11

Keywords

  • Differential evolution
  • Evolutionary algorithms
  • Jumping gene
  • Optimization

ASJC Scopus subject areas

  • Artificial Intelligence

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