An efficient archive-based parameter-free multi-objective Rao-DE algorithm for bi-objective optimization of truss structures
•An archive-based parameter-free multi-objective Rao-Differential Evolution (APMORD) algorithm has been proposed.•The external best archive and dynamic archive-based method have been proposed to improve APMORD's performance.•Eight benchmark truss structure problems have been studied to demonstr...
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| Published in | Computers & structures Vol. 308; p. 107647 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.02.2025
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0045-7949 |
| DOI | 10.1016/j.compstruc.2025.107647 |
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| Abstract | •An archive-based parameter-free multi-objective Rao-Differential Evolution (APMORD) algorithm has been proposed.•The external best archive and dynamic archive-based method have been proposed to improve APMORD's performance.•Eight benchmark truss structure problems have been studied to demonstrate the efficiency of APMORD.
Metaheuristic algorithms have proven effective for complex optimization problems, including truss design, yet many require specific parameter settings, leading to increased complexity. This paper proposes an archive-based parameter-free multi-objective Rao-Differential Evolution (APMORD) algorithm for bi-objective optimization of truss design problems. APMORD simplifies the process by integrating the Rao-1 mutation technique with the differential evolution (DE) framework, eliminating the need for specific parameter setups. An external best archive (BA) enhances the diversity and distribution of the Pareto set, while the dynamic archive-based method (dynABM) adjusts the population size to improve optimization efficiency. The performance of APMORD is evaluated across eight classical truss structure problems using several indicators, showcasing its superior effectiveness compared to recent metaheuristic techniques, especially in achieving a broader spread of optimal solutions. Furthermore, sensitivity analysis indicates that decreasing the population size while increasing the archive size significantly enhances the algorithm’s performance and improves the quality of the optimal solution set. These findings highlight APMORD’s contribution to advancing optimization strategies for truss structures, emphasizing its efficiency and adaptability in various optimization scenarios. |
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| AbstractList | •An archive-based parameter-free multi-objective Rao-Differential Evolution (APMORD) algorithm has been proposed.•The external best archive and dynamic archive-based method have been proposed to improve APMORD's performance.•Eight benchmark truss structure problems have been studied to demonstrate the efficiency of APMORD.
Metaheuristic algorithms have proven effective for complex optimization problems, including truss design, yet many require specific parameter settings, leading to increased complexity. This paper proposes an archive-based parameter-free multi-objective Rao-Differential Evolution (APMORD) algorithm for bi-objective optimization of truss design problems. APMORD simplifies the process by integrating the Rao-1 mutation technique with the differential evolution (DE) framework, eliminating the need for specific parameter setups. An external best archive (BA) enhances the diversity and distribution of the Pareto set, while the dynamic archive-based method (dynABM) adjusts the population size to improve optimization efficiency. The performance of APMORD is evaluated across eight classical truss structure problems using several indicators, showcasing its superior effectiveness compared to recent metaheuristic techniques, especially in achieving a broader spread of optimal solutions. Furthermore, sensitivity analysis indicates that decreasing the population size while increasing the archive size significantly enhances the algorithm’s performance and improves the quality of the optimal solution set. These findings highlight APMORD’s contribution to advancing optimization strategies for truss structures, emphasizing its efficiency and adaptability in various optimization scenarios. |
| ArticleNumber | 107647 |
| Author | Tangaramvong, Sawekchai Su, Rut Pham, Hoang-Anh Nguyen, Manh-Cuong Truong, Viet-Hung |
| Author_xml | – sequence: 1 givenname: Viet-Hung surname: Truong fullname: Truong, Viet-Hung organization: Faculty of Civil Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 100000, Viet Nam – sequence: 2 givenname: Sawekchai surname: Tangaramvong fullname: Tangaramvong, Sawekchai email: sawekchai.t@chula.ac.th organization: Center of Excellence in Applied Mechanics and Structures, Department of Civil Engineering, Chulalongkorn University, Bangkok 10330, Thailand – sequence: 3 givenname: Hoang-Anh surname: Pham fullname: Pham, Hoang-Anh organization: Department of Structural Mechanics, Hanoi University of Civil Engineering, 55 Giai Phong, Hanoi 100000, Viet Nam – sequence: 4 givenname: Manh-Cuong surname: Nguyen fullname: Nguyen, Manh-Cuong organization: Faculty of Civil Engineering, Thuyloi University, 175 Tay Son, Dong Da, Hanoi 100000, Viet Nam – sequence: 5 givenname: Rut surname: Su fullname: Su, Rut organization: Center of Excellence in Applied Mechanics and Structures, Department of Civil Engineering, Chulalongkorn University, Bangkok 10330, Thailand |
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