{"title":"An improved newton metaheuristic algorithm for design optimization of steel moment-resisting frames","authors":"Ataollah Zaerreza, Saeed Gholizadeh, Mirali Mohammadi","doi":"10.1016/j.advengsoft.2025.103960","DOIUrl":null,"url":null,"abstract":"<div><div>This paper proposes an improved Newton metaheuristic algorithm (INMA) for solving steel moment resisting frame optimization problems. The proposed INMA uses a novel initialization scheme that produces an efficient initial population that is significantly better than a randomly generated initial population for structural optimization problems. The efficiency of the algorithm is further improved by the implementation of a statistical regeneration mechanism. The effectiveness of the INMA is initially demonstrated through two benchmark optimization problems involving steel moment-resisting frames. Furthermore, the performance of the INMA is evaluated to address the performance-based design optimization problem of steel moment-resisting frames. Due to the potentially extensive computational time of the performance-based design optimization process, a nonlinear static pushover analysis is performed to determine structural responses at various seismic performance levels. The numerical results indicate that the INMA outperforms other algorithms in the literature.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"207 ","pages":"Article 103960"},"PeriodicalIF":5.7000,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Engineering Software","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0965997825000985","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes an improved Newton metaheuristic algorithm (INMA) for solving steel moment resisting frame optimization problems. The proposed INMA uses a novel initialization scheme that produces an efficient initial population that is significantly better than a randomly generated initial population for structural optimization problems. The efficiency of the algorithm is further improved by the implementation of a statistical regeneration mechanism. The effectiveness of the INMA is initially demonstrated through two benchmark optimization problems involving steel moment-resisting frames. Furthermore, the performance of the INMA is evaluated to address the performance-based design optimization problem of steel moment-resisting frames. Due to the potentially extensive computational time of the performance-based design optimization process, a nonlinear static pushover analysis is performed to determine structural responses at various seismic performance levels. The numerical results indicate that the INMA outperforms other algorithms in the literature.
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.