全局优化工程设计问题的沙猫算法优化

IF 4.8 2区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Journal of Computational Design and Engineering Pub Date : 2023-10-17 DOI:10.1093/jcde/qwad094

Shuilin Chen, Jianguo Zheng

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引用次数: 0

摘要

摘要沙猫群优化算法(SCSO)是近年来兴起的一种流行的群智能元启发式算法，存在收敛精度低和容易陷入局部最优的两大局限性。为了解决这些问题，本文提出了一种基于算法优化算法(AOA)、基于折射对立学习和交叉策略的改进SCSO算法，称为沙猫算法优化算法(SC-AOA)，该算法引入AOA来平衡探索和开发，减少陷入局部最优的可能性，使用交叉策略来提高收敛精度。通过10个基准功能、CEC 2014、CEC 2017、CEC 2022和8个工程问题对SC-AOA的有效性进行了基准测试。结果表明，SC-AOA具有较好的性能。

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Sand Cat Arithmetic Optimization Algorithm for Global Optimization Engineering Design Problems

Abstract Sand cat swarm optimization (SCSO) is a recently introduced popular swarm intelligence metaheuristic algorithm, which has two significant limitations – low convergence accuracy and the tendency to get stuck in local optima. To alleviate these issues, this paper proposes an improved SCSO based on the arithmetic optimization algorithm (AOA), the refracted opposition-based learning and crisscross strategy, called the sand cat arithmetic optimization algorithm (SC-AOA), which introduced AOA to balance the exploration and exploitation and reduce the possibility of falling into the local optimum, used crisscross strategy to enhance convergence accuracy. The effectiveness of SC-AOA is benchmarked on 10 benchmark functions, CEC 2014, CEC 2017, CEC 2022, and eight engineering problems. The results show that the SC-AOA has a competitive performance.

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来源期刊

Journal of Computational Design and Engineering Computer Science-Human-Computer Interaction

CiteScore

7.70

自引率

20.40%

发文量

125

期刊介绍： Journal of Computational Design and Engineering is an international journal that aims to provide academia and industry with a venue for rapid publication of research papers reporting innovative computational methods and applications to achieve a major breakthrough, practical improvements, and bold new research directions within a wide range of design and engineering: • Theory and its progress in computational advancement for design and engineering • Development of computational framework to support large scale design and engineering • Interaction issues among human, designed artifacts, and systems • Knowledge-intensive technologies for intelligent and sustainable systems • Emerging technology and convergence of technology fields presented with convincing design examples • Educational issues for academia, practitioners, and future generation • Proposal on new research directions as well as survey and retrospectives on mature field.