Real‐World Steel Frame Optimization Using a Hybrid Leader Selection‐Based Multi‐Objective Flow Direction Algorithm
ABSTRACT This paper presents a novel Multi‐Objective Flow Direction Algorithm (MOFDA) for complex engineering optimization problems. The key innovation is a hybrid leader selection mechanism, which replaces the conventional roulette wheel selection and significantly enhances convergence and diversit...
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| Published in | International journal for numerical methods in engineering Vol. 126; no. 15 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Hoboken, USA
John Wiley & Sons, Inc
15.08.2025
Wiley Subscription Services, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0029-5981 1097-0207 |
| DOI | 10.1002/nme.70098 |
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| Abstract | ABSTRACT
This paper presents a novel Multi‐Objective Flow Direction Algorithm (MOFDA) for complex engineering optimization problems. The key innovation is a hybrid leader selection mechanism, which replaces the conventional roulette wheel selection and significantly enhances convergence and diversity in identifying Pareto‐optimal solutions. The proposed MOFDA is rigorously evaluated on 31 standard benchmark problems and 11 constrained engineering design cases—including truss optimization, welded beam design, and a large‐scale steel frame structure—to assess its accuracy, stability, and solution diversity comprehensively. Comparative studies with state‐of‐the‐art multi‐objective algorithms such as MOMVO, MOMSA, MSSA, and MOGNDO further highlight the strong performance of MOFDA. In addition, MOFDA is integrated into a MATLAB–SAP2000 framework and applied to the real‐world structural optimization of the Dong Bai ferry terminal steel frame in Vietnam. The results show that MOFDA consistently achieves competitive or superior outcomes on benchmark functions, delivers substantial weight reduction, and improves structural efficiency in engineering applications. These findings demonstrate both the proposed approach's technical novelty and practical effectiveness. Source codes of MOFDA is publicly available at
https://ceats.ou.edu.vn/us/codes.html. |
|---|---|
| AbstractList | ABSTRACT
This paper presents a novel Multi‐Objective Flow Direction Algorithm (MOFDA) for complex engineering optimization problems. The key innovation is a hybrid leader selection mechanism, which replaces the conventional roulette wheel selection and significantly enhances convergence and diversity in identifying Pareto‐optimal solutions. The proposed MOFDA is rigorously evaluated on 31 standard benchmark problems and 11 constrained engineering design cases—including truss optimization, welded beam design, and a large‐scale steel frame structure—to assess its accuracy, stability, and solution diversity comprehensively. Comparative studies with state‐of‐the‐art multi‐objective algorithms such as MOMVO, MOMSA, MSSA, and MOGNDO further highlight the strong performance of MOFDA. In addition, MOFDA is integrated into a MATLAB–SAP2000 framework and applied to the real‐world structural optimization of the Dong Bai ferry terminal steel frame in Vietnam. The results show that MOFDA consistently achieves competitive or superior outcomes on benchmark functions, delivers substantial weight reduction, and improves structural efficiency in engineering applications. These findings demonstrate both the proposed approach's technical novelty and practical effectiveness. Source codes of MOFDA is publicly available at
https://ceats.ou.edu.vn/us/codes.html. This paper presents a novel Multi‐Objective Flow Direction Algorithm (MOFDA) for complex engineering optimization problems. The key innovation is a hybrid leader selection mechanism, which replaces the conventional roulette wheel selection and significantly enhances convergence and diversity in identifying Pareto‐optimal solutions. The proposed MOFDA is rigorously evaluated on 31 standard benchmark problems and 11 constrained engineering design cases—including truss optimization, welded beam design, and a large‐scale steel frame structure—to assess its accuracy, stability, and solution diversity comprehensively. Comparative studies with state‐of‐the‐art multi‐objective algorithms such as MOMVO, MOMSA, MSSA, and MOGNDO further highlight the strong performance of MOFDA. In addition, MOFDA is integrated into a MATLAB–SAP2000 framework and applied to the real‐world structural optimization of the Dong Bai ferry terminal steel frame in Vietnam. The results show that MOFDA consistently achieves competitive or superior outcomes on benchmark functions, delivers substantial weight reduction, and improves structural efficiency in engineering applications. These findings demonstrate both the proposed approach's technical novelty and practical effectiveness. Source codes of MOFDA is publicly available at https://ceats.ou.edu.vn/us/codes.html . |
| Author | Khatir, Samir Cuong‐Le, Thanh Vu‐Huu, Truong |
| Author_xml | – sequence: 1 givenname: Truong surname: Vu‐Huu fullname: Vu‐Huu, Truong organization: Center for Engineering Application and Technology Solutions, Ho Chi Minh City Open University – sequence: 2 givenname: Samir surname: Khatir fullname: Khatir, Samir organization: Center for Engineering Application and Technology Solutions, Ho Chi Minh City Open University – sequence: 3 givenname: Thanh orcidid: 0000-0001-6828-0879 surname: Cuong‐Le fullname: Cuong‐Le, Thanh email: cuong.lt@ou.edu.vn organization: Center for Engineering Application and Technology Solutions, Ho Chi Minh City Open University |
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This paper presents a novel Multi‐Objective Flow Direction Algorithm (MOFDA) for complex engineering optimization problems. The key innovation is a... This paper presents a novel Multi‐Objective Flow Direction Algorithm (MOFDA) for complex engineering optimization problems. The key innovation is a hybrid... |
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| SubjectTerms | Algorithms Benchmarks Comparative studies Design engineering Design optimization Ferries flow direction algorithm Frame structures indicators metaheuristics multi‐objective optimization Optimization Steel frames Weight reduction |
| Title | Real‐World Steel Frame Optimization Using a Hybrid Leader Selection‐Based Multi‐Objective Flow Direction Algorithm |
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