Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversity
The challenge of achieving equilibrium between exploration and exploitation stands as a critical barrier in multi-objective metaheuristic optimization when applied to complex engineering problems such as truss structure design. The Multi-Objective Weighted Average Algorithm (MOWAA) presents a new me...
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Elsevier
2025-03-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025003275 |
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| author | Divya Adalja Kanak Kalita Lenka Čepová Pinank Patel Nikunj Mashru Pradeep Jangir Arpita |
| author_facet | Divya Adalja Kanak Kalita Lenka Čepová Pinank Patel Nikunj Mashru Pradeep Jangir Arpita |
| author_sort | Divya Adalja |
| collection | DOAJ |
| description | The challenge of achieving equilibrium between exploration and exploitation stands as a critical barrier in multi-objective metaheuristic optimization when applied to complex engineering problems such as truss structure design. The Multi-Objective Weighted Average Algorithm (MOWAA) presents a new methodology which employs adaptive weighted average position control to optimize population movement for enhanced solution quality. The performance evaluation of MOWAA relies on benchmarking it against five state-of-the-art multi-objective optimization algorithms NSGA-II, MOEA/D, MOLCA, MOEDO and MORIME through eight truss structure optimization problems of increasing complexity. The evaluation of performance relies on three key metrics: Hypervolume (HV), Inverted Generational Distance (IGD) and Spacing (SP). MOWAA demonstrates superior performance compared to competing algorithms through its ability to generate Pareto fronts with higher HV values and lower IGD values and more uniform distribution. The enhanced performance of MOWAA demonstrates its superior capability to efficiently explore the objective space for finding optimal weight-minimization and compliance trade-offs. The robustness of MOWAA is proven through statistical validation with the Friedman rank test which establishes MOWAA as the leading approach with statistically significant advantages. MOWAA demonstrates runtime efficiency throughout truss optimization tasks of varying sizes which enables its practical application for real-world structural optimization problems. MOWAA emerges as a sophisticated and efficient optimization method which demonstrates strong capabilities for engineering applications and computational design. |
| format | Article |
| id | doaj-art-c8a08afcd93a4ebf967de581d532b0c2 |
| institution | DOAJ |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-c8a08afcd93a4ebf967de581d532b0c22025-08-20T03:00:34ZengElsevierResults in Engineering2590-12302025-03-012510424110.1016/j.rineng.2025.104241Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversityDivya Adalja0Kanak Kalita1Lenka Čepová2Pinank Patel3Nikunj Mashru4Pradeep Jangir5 Arpita6Department of Mathematics, Marwadi University, Rajkot 360003, IndiaDepartment of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi 600 062, India; Department of Machining, Assembly and Engineering Metrology, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic; Corresponding author.Department of Machining, Assembly and Engineering Metrology, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 70800 Ostrava, Czech RepublicDepartment of Mechanical Engineering, Marwadi University, Rajkot 360003, IndiaDepartment of Mechanical Engineering, Marwadi University, Rajkot 360003, IndiaUniversity Centre for Research and Development, Chandigarh University, Mohali 140413, India; Department of CSE, Graphic Era Hill University, Dehradun, 248002, India; Applied Science Research Center, Applied Science Private University, Amman 11931, Jordan; Centre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, 140401, Punjab, IndiaDepartment of Biosciences, Saveetha School of Engineering. Saveetha Institute of Medical and Technical Sciences, Chennai 602 105, IndiaThe challenge of achieving equilibrium between exploration and exploitation stands as a critical barrier in multi-objective metaheuristic optimization when applied to complex engineering problems such as truss structure design. The Multi-Objective Weighted Average Algorithm (MOWAA) presents a new methodology which employs adaptive weighted average position control to optimize population movement for enhanced solution quality. The performance evaluation of MOWAA relies on benchmarking it against five state-of-the-art multi-objective optimization algorithms NSGA-II, MOEA/D, MOLCA, MOEDO and MORIME through eight truss structure optimization problems of increasing complexity. The evaluation of performance relies on three key metrics: Hypervolume (HV), Inverted Generational Distance (IGD) and Spacing (SP). MOWAA demonstrates superior performance compared to competing algorithms through its ability to generate Pareto fronts with higher HV values and lower IGD values and more uniform distribution. The enhanced performance of MOWAA demonstrates its superior capability to efficiently explore the objective space for finding optimal weight-minimization and compliance trade-offs. The robustness of MOWAA is proven through statistical validation with the Friedman rank test which establishes MOWAA as the leading approach with statistically significant advantages. MOWAA demonstrates runtime efficiency throughout truss optimization tasks of varying sizes which enables its practical application for real-world structural optimization problems. MOWAA emerges as a sophisticated and efficient optimization method which demonstrates strong capabilities for engineering applications and computational design.http://www.sciencedirect.com/science/article/pii/S2590123025003275Meta-heuristic optimizationWeighted average positionTruss structuresPerformance metricsMulti-objective |
| spellingShingle | Divya Adalja Kanak Kalita Lenka Čepová Pinank Patel Nikunj Mashru Pradeep Jangir Arpita Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversity Results in Engineering Meta-heuristic optimization Weighted average position Truss structures Performance metrics Multi-objective |
| title | Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversity |
| title_full | Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversity |
| title_fullStr | Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversity |
| title_full_unstemmed | Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversity |
| title_short | Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversity |
| title_sort | advancing truss structure optimization a multi objective weighted average algorithm with enhanced convergence and diversity |
| topic | Meta-heuristic optimization Weighted average position Truss structures Performance metrics Multi-objective |
| url | http://www.sciencedirect.com/science/article/pii/S2590123025003275 |
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