Reducing the Price of Stable Cable Stayed Bridges with CMA-ES

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Applications of Evolutionary Computation (EvoApplications 2023)

Abstract

The design of cable-stayed bridges requires the determination of several design variables’ values. Civil engineers usually perform this task by hand as an iteration of steps that stops when the engineer is happy with both the cost and maintaining the structural constraints of the solution. The problem’s difficulty arises from the fact that changing a variable may affect other variables, meaning that they are not independent, suggesting that we are facing a deceptive landscape.

In this work, we compare two approaches to a baseline solution: a Genetic Algorithm and a CMA-ES algorithm. There are two objectives when designing the bridges: minimizing the cost and maintaining the structural constraints in acceptable values to be considered safe. These are conflicting objectives, meaning that decreasing the cost often results in a bridge that is not structurally safe. The results suggest that CMA-ES is a better option for finding good solutions in the search space, beating the baseline with the same amount of evaluations, while the Genetic Algorithm could not. In concrete, the CMA-ES approach is able to design bridges that are cheaper and structurally safe.

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Acknowledgements

This research was partially funded by the project grant BEIS (Bridge Engineering Information System), supported by Operational Programme for Competitiveness and Internationalisation (COMPETE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF) and by the FCT - Foundation for Science and Technology, I.P./MCTES through national funds (PIDDAC), within the scope of CISUC R &D Unit - UIDB/00326/2020 or project code UIDP/00326/2020*.

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Correspondence to João Correia .

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Fernandes, G., Lourenço, N., Correia, J. (2023). Reducing the Price of Stable Cable Stayed Bridges with CMA-ES. In: Correia, J., Smith, S., Qaddoura, R. (eds) Applications of Evolutionary Computation. EvoApplications 2023. Lecture Notes in Computer Science, vol 13989. Springer, Cham. https://doi.org/10.1007/978-3-031-30229-9_15

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  • DOI: https://doi.org/10.1007/978-3-031-30229-9_15

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