Information acquisition optimizer: a new efficient algorithm for solving numerical and constrained engineering optimization problems

This paper addresses the increasing complexity of challenges in the field of continuous nonlinear optimization by proposing an innovative algorithm called information acquisition optimizer (IAO), which is inspired by human information acquisition behaviors and consists of three crucial strategies: i...

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Veröffentlicht in:The Journal of supercomputing Jg. 80; H. 18; S. 25736 - 25791
Hauptverfasser: Wu, Xiao, Li, Shaobo, Jiang, Xinghe, Zhou, Yanqiu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.12.2024
Springer Nature B.V
Schlagworte:
Algorithms
Compilers
Complexity
Computer Science
Data analysis
Data processing
Efficiency
Engineering
Foraging behavior
Interpreters
Optimization
Optimization algorithms
Processor Architectures
Programming Languages
Rank tests
Traveling salesman problem
Information collection
Information acquisition optimizer
Information analysis and organization
Information filtering and evaluation
Continuous nonlinear optimization
ISSN:0920-8542, 1573-0484
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Zusammenfassung:This paper addresses the increasing complexity of challenges in the field of continuous nonlinear optimization by proposing an innovative algorithm called information acquisition optimizer (IAO), which is inspired by human information acquisition behaviors and consists of three crucial strategies: information collection, information filtering and evaluation, and information analysis and organization to accommodate diverse optimization requirements. Firstly, comparative assessments of performance are conducted between the IAO and 15 widely recognized algorithms using the standard test function suites from CEC2014, CEC2017, CEC2020, and CEC2022. The results demonstrate that IAO is robustly competitive regarding convergence rate, solution accuracy, and stability. Additionally, the outcomes of the Wilcoxon signed rank test and Friedman mean ranking strongly validate the effectiveness and reliability of IAO. Moreover, the time comparison analysis experiments indicate its high efficiency. Finally, comparative tests on five real-world optimization difficulties affirm the remarkable applicability of IAO in handling complex issues with unknown search spaces. The code for the IAO algorithm is available at https://ww2.mathworks.cn/matlabcentral/fileexchange/169331-information-acquisition-optimizer .
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-024-06384-3