Multi-objective optimization for bridge and viaduct design: case study

Abstract

Abstract: This article presents the application of the Multiple Objective Particle Swarm Optimization (MOPSO) method, enhanced with specifically tuned parameters using the Taguchi method, for optimizing bridge and viaduct designs. Unlike conventional approaches, the optimization in this study encompasses the entire structure rather than focusing solely on the deck. This approach is illustrated through case studies on two viaducts located in Atalaia and Mandaguaçu along the BR-376 highway in Paraná, Brazil. In Atalaia, the optimized solutions achieved reductions in construction costs by 10.5% to 22.7%, CO2 emissions by 8.9% to 21.2%, and extended the design service life by 24.0% to 540.7%. Similarly, in Mandaguaçu, the optimizations resulted in cost reductions ranging from 9.1% to 23.2%, decreases in CO2 emissions from 12.7% to 23.5%, and increases in the design service life by up to 540.7%. The study also revealed consistent patterns between the degrees of freedom and objective functions; specifically, larger cross-sectional dimensions tended to lower costs, while smaller dimensions were associated with reduced CO2 emissions. These findings illustrate the real-world performance improvements afforded by the optimization process, which not only reduces the global cost per year of service compared to the original designs but also enhances economic and environmental performance, thereby demonstrating the effectiveness of MOPSO in structural optimization for sustainable infrastructure development.

Keywords

• bridge
• viaduct
• multiple objective particle swarm optimization
• structural optimization
• sustainable infrastructure development