Multi-population cooperative teaching–learning-based optimization for nonlinear equation systems
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 (crowdi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2023-05-01
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| Series: | Complex & Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40747-023-01074-8 |
| _version_ | 1797647093242789888 |
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| author | Liao Zuowen Li Shuijia Gong Wenyin Gu Qiong |
| author_facet | Liao Zuowen Li Shuijia Gong Wenyin Gu Qiong |
| author_sort | Liao Zuowen |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T15:12:21Z |
| format | Article |
| id | doaj.art-066e41b7b026471382aa7c92596d998d |
| institution | Directory Open Access Journal |
| issn | 2199-4536 2198-6053 |
| language | English |
| last_indexed | 2024-03-11T15:12:21Z |
| publishDate | 2023-05-01 |
| publisher | Springer |
| record_format | Article |
| series | Complex & Intelligent Systems |
| spelling | doaj.art-066e41b7b026471382aa7c92596d998d2023-10-29T12:41:07ZengSpringerComplex & Intelligent Systems2199-45362198-60532023-05-01966593660910.1007/s40747-023-01074-8Multi-population cooperative teaching–learning-based optimization for nonlinear equation systemsLiao Zuowen0Li Shuijia1Gong Wenyin2Gu Qiong3Beibu Gulf Ocean Development Research Center, Beibu Gulf UniversitySchool of Computer Science, China University of GeosciencesSchool of Computer Science, China University of GeosciencesSchool of Computer Engineering, Hubei University of Arts and ScienceAbstract 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.https://doi.org/10.1007/s40747-023-01074-8Nonlinear equation systemsmulti-population cooperationteaching–learning-based optimizationniching techniqueadaptive selection scheme |
| spellingShingle | Liao Zuowen Li Shuijia Gong Wenyin Gu Qiong Multi-population cooperative teaching–learning-based optimization for nonlinear equation systems Complex & Intelligent Systems Nonlinear equation systems multi-population cooperation teaching–learning-based optimization niching technique adaptive selection scheme |
| title | Multi-population cooperative teaching–learning-based optimization for nonlinear equation systems |
| title_full | Multi-population cooperative teaching–learning-based optimization for nonlinear equation systems |
| title_fullStr | Multi-population cooperative teaching–learning-based optimization for nonlinear equation systems |
| title_full_unstemmed | Multi-population cooperative teaching–learning-based optimization for nonlinear equation systems |
| title_short | Multi-population cooperative teaching–learning-based optimization for nonlinear equation systems |
| title_sort | multi population cooperative teaching learning based optimization for nonlinear equation systems |
| topic | Nonlinear equation systems multi-population cooperation teaching–learning-based optimization niching technique adaptive selection scheme |
| url | https://doi.org/10.1007/s40747-023-01074-8 |
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