DOAJ Open Access 2023

Multi-population cooperative teaching–learning-based optimization for nonlinear equation systems

Liao Zuowen Li Shuijia Gong Wenyin Gu Qiong

Abstrak

Abstract Solving nonlinear equation systems (NESs) requires locating different roots in one run. To effectively deal with NESs, a multi-population cooperative teaching–learning-based optimization, named MCTLBO, is presented. The innovations of MCTLBO are as follows: (i) two niching technique (crowding and improved speciation) are integrated into the algorithm to enhance population diversity; (ii) an adaptive selection scheme is proposed to select the learning rules in the teaching phase; (iii) the new learning rules based on experience learning are developed to promote the search efficiency in the teaching and learning phases. MCTLBO was tested on 30 classical problems and the experimental results show that MCTLBO has better root finding performance than other algorithms. In addition, MCTLBO achieves competitive results in eighteen new test sets.

Penulis (4)

L

Liao Zuowen

L

Li Shuijia

G

Gong Wenyin

G

Gu Qiong

Format Sitasi

Zuowen, L., Shuijia, L., Wenyin, G., Qiong, G. (2023). Multi-population cooperative teaching–learning-based optimization for nonlinear equation systems. https://doi.org/10.1007/s40747-023-01074-8

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Informasi Jurnal
Tahun Terbit
2023
Sumber Database
DOAJ
DOI
10.1007/s40747-023-01074-8
Akses
Open Access ✓