A novel electrons drifting algorithm for non-linear optimization problems

Jian Tang Liao, Hong Tzer Yang

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

1 Citation (Scopus)

Abstract

In response to higher and higher dimensions and complexity of optimization problems in engineering applications, the optimization algorithms face more and more challenges. This paper proposes a novel electron drifting algorithm (e-DA) to avoid the common disadvantages, such as easy to trap in a local optimal point and sensitive to initial solutions, of existing methods. A simple example is addressed in the paper to make readers easily understand the executed processes. Some benchmark functions are used for testing the effectiveness of the proposed e-DA. Besides, the performance of e-DA is compared with the existing optimization algorithms, including particle swarm optimization (PSO), differential evolution (DE), and artificial bee colony (ABC). Numerical results verify that the searching efficiency and capability of the proposed e-DA are enhanced and better than the existing algorithms.

Original languageEnglish
Title of host publication2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016
EditorsJiayi Du, Chubo Liu, Kenli Li, Lipo Wang, Zhao Tong, Maozhen Li, Ning Xiong
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages155-160
Number of pages6
ISBN (Electronic)9781509040933
DOIs
Publication statusPublished - 2016 Oct 19
Event12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016 - Changsha, China
Duration: 2016 Aug 132016 Aug 15

Publication series

Name2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016

Other

Other12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016
CountryChina
CityChangsha
Period16-08-1316-08-15

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Control and Optimization
  • Computer Science Applications
  • Signal Processing

Cite this

Liao, J. T., & Yang, H. T. (2016). A novel electrons drifting algorithm for non-linear optimization problems. In J. Du, C. Liu, K. Li, L. Wang, Z. Tong, M. Li, & N. Xiong (Eds.), 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016 (pp. 155-160). [7603167] (2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FSKD.2016.7603167