Polygene-based evolutionary algorithms with frequent pattern mining

doi:10.1007/s11704-016-6104-3

Front. Comput. Sci.

2018, Vol. 12

Issue (5) : 950-965 https://doi.org/10.1007/s11704-016-6104-3

RESEARCH ARTICLE

Polygene-based evolutionary algorithms with frequent pattern mining

Shuaiqiang WANG^1,²(

), Yilong YIN³(

)

¹. Research Center of Big Data Applications, Qilu University of Technology, Jinan 250100, China
². Department of Computer Science and Information Systems, University of Jyvaskyla, Jyvaskyla 40014, Finland
³. School of Computer Science and Technology, Shandong University, Jinan 250101, China

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Abstract

In this paper, we introduce polygene-based evolution, a novel framework for evolutionary algorithms (EAs) that features distinctive operations in the evolutionary process. In traditional EAs, the primitive evolution unit is a gene, wherein genes are independent components during evolution. In polygene-based evolutionary algorithms (PGEAs), the evolution unit is a polygene, i.e., a set of co-regulated genes. Discovering and maintaining quality polygenes can play an effective role in evolving quality individuals. Polygenes generalize genes, and PGEAs generalize EAs. Implementing the PGEA framework involves three phases: (I) polygene discovery, (II) polygene planting, and (III) polygene-compatible evolution. For Phase I, we adopt an associative classificationbased approach to discover quality polygenes. For Phase II, we perform probabilistic planting to maintain the diversity of individuals. For Phase III, we incorporate polygenecompatible crossover and mutation in producing the next generation of individuals. Extensive experiments on function optimization benchmarks in comparison with the conventional and state-of-the-art EAs demonstrate the potential of the approach in terms of accuracy and efficiency improvement.

Keywords polygenes evolutionary algorithms function optimization associative classification data mining

Corresponding Author(s): Shuaiqiang WANG

Just Accepted Date: 19 October 2016 Online First Date: 06 March 2018 Issue Date: 21 September 2018

Cite this article:

Shuaiqiang WANG,Yilong YIN. Polygene-based evolutionary algorithms with frequent pattern mining[J]. Front. Comput. Sci., 2018, 12(5): 950-965.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-016-6104-3
https://academic.hep.com.cn/fcs/EN/Y2018/V12/I5/950

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