Nonlinear Equations Solving with Intelligent Optimization Algorithms: A Survey
Nonlinear Equations (NEs), which may usually have multiple roots, are ubiquitous in diverse fields. One of the main purposes of solving NEs is to locate as many roots as possible simultaneously in a single run, however, it is a difficult and challenging task in numerical computation. In recent years...
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| Vydáno v: | Complex System Modeling and Simulation Ročník 1; číslo 1; s. 15 - 32 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Tsinghua University Press
01.03.2021
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| ISSN: | 2096-9929, 2096-9929 |
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| Abstract | Nonlinear Equations (NEs), which may usually have multiple roots, are ubiquitous in diverse fields. One of the main purposes of solving NEs is to locate as many roots as possible simultaneously in a single run, however, it is a difficult and challenging task in numerical computation. In recent years, Intelligent Optimization Algorithms (IOAs) have shown to be particularly effective in solving NEs. This paper provides a comprehensive survey on IOAs that have been exploited to locate multiple roots of NEs. This paper first revisits the fundamental definition of NEs and reviews the most recent development of the transformation techniques. Then, solving NEs with IOAs is reviewed, followed by the benchmark functions and the performance comparison of several state-of-the-art algorithms. Finally, this paper points out the challenges and some possible open issues for solving NEs. |
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| AbstractList | Nonlinear Equations (NEs), which may usually have multiple roots, are ubiquitous in diverse fields. One of the main purposes of solving NEs is to locate as many roots as possible simultaneously in a single run, however, it is a difficult and challenging task in numerical computation. In recent years, Intelligent Optimization Algorithms (IOAs) have shown to be particularly effective in solving NEs. This paper provides a comprehensive survey on IOAs that have been exploited to locate multiple roots of NEs. This paper first revisits the fundamental definition of NEs and reviews the most recent development of the transformation techniques. Then, solving NEs with IOAs is reviewed, followed by the benchmark functions and the performance comparison of several state-of-the-art algorithms. Finally, this paper points out the challenges and some possible open issues for solving NEs. |
| Author | Gong, Wenyin Guo, Yuanyuan Liao, Zuowen Mi, Xianyan Wang, Ling |
| Author_xml | – sequence: 1 givenname: Wenyin surname: Gong fullname: Gong, Wenyin – sequence: 2 givenname: Zuowen surname: Liao fullname: Liao, Zuowen – sequence: 3 givenname: Xianyan surname: Mi fullname: Mi, Xianyan – sequence: 4 givenname: Ling surname: Wang fullname: Wang, Ling – sequence: 5 givenname: Yuanyuan surname: Guo fullname: Guo, Yuanyuan |
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