Mirage search optimization: Application to path planning and engineering design problems

IF 5.7 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software Pub Date : 2025-02-18 DOI:10.1016/j.advengsoft.2025.103883

Jiahao He , Shijie Zhao , Jiayi Ding , Yiming Wang

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引用次数: 0

Abstract

In this article, a new meta-heuristic optimization algorithm motivated by mirage physical principles, named Mirage Search Optimization (MSO), is proposed. MSO mainly consists of two updating strategies, i.e., the superior mirage strategy and the inferior mirage strategy, which results in the global exploration and local exploitation capabilities, respectively. In addition, other two population evolution-guided mechanisms such as the fitness-distance balance (FDB) and fitness-distance constraint (FDC) are incorporated into MSO and termed as FDB-MSO and FDC-MSO, to further check and test the good optimization performance of MSO and its variants. MSO and 25 comparison algorithms are examined on CEC2017, CEC2014 and 21 classical benchmark functions. Optimization efficiency of MSO was verified by Wilcoxon rank sum test, Friedman test and stability analysis. Furthermore, competitiveness of MSO in solving real-world problems under constraints is demonstrated using six classical engineering problems. Finally, MSO is used for the path planning problem, which verifies applicability of MSO to real-world problems. Experimental results indicate MSO is competitive with other competing algorithms. Source codes of MSO are publicly available at https://www.mathworks.com/matlabcentral/fileexchange/180042-mirage-search-optimization.

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幻影搜索优化：在路径规划和工程设计问题中的应用

本文提出了一种基于海市蜃楼物理原理的元启发式优化算法——海市蜃楼搜索优化（MSO）。MSO主要包括两种更新策略，即上级海市蜃楼策略和下级海市蜃楼策略，分别具有全局探索能力和局部开发能力。此外，将适应度-距离平衡（FDB）和适应度-距离约束（FDC）两种种群进化导向机制引入到MSO中，分别称为FDB-MSO和FDC-MSO，进一步检验MSO及其变体的良好优化性能。在CEC2017、CEC2014和21个经典基准函数上对MSO和25种比较算法进行了检验。通过Wilcoxon秩和检验、Friedman检验和稳定性分析验证了MSO的优化效率。此外，通过六个经典工程问题，证明了MSO在解决约束条件下的现实问题时的竞争力。最后，将粒子群算法应用于路径规划问题，验证了粒子群算法在实际问题中的适用性。实验结果表明，MSO算法具有较强的竞争力。MSO的源代码可在https://www.mathworks.com/matlabcentral/fileexchange/180042-mirage-search-optimization上公开获得。

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来源期刊

Advances in Engineering Software 工程技术-计算机：跨学科应用

CiteScore

7.70

自引率

4.20%

发文量

169

审稿时长

37 days

期刊介绍： The objective of this journal is to communicate recent and projected advances in computer-based engineering techniques. The fields covered include mechanical, aerospace, civil and environmental engineering, with an emphasis on research and development leading to practical problem-solving. The scope of the journal includes: • Innovative computational strategies and numerical algorithms for large-scale engineering problems • Analysis and simulation techniques and systems • Model and mesh generation • Control of the accuracy, stability and efficiency of computational process • Exploitation of new computing environments (eg distributed hetergeneous and collaborative computing) • Advanced visualization techniques, virtual environments and prototyping • Applications of AI, knowledge-based systems, computational intelligence, including fuzzy logic, neural networks and evolutionary computations • Application of object-oriented technology to engineering problems • Intelligent human computer interfaces • Design automation, multidisciplinary design and optimization • CAD, CAE and integrated process and product development systems • Quality and reliability.