Multi-objective optimization for cost-effective aseismic design of submerged floating tunnels considering weighted preferences

In aseismic design of the submerged floating tunnel (SFT), both the seismic response and construction cost should be considered and optimized to achieve a balance between structural safety and project investment. To realize the simultaneous optimization of several design objectives, this study propo...

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Main Authors: He, Renfei, Zhang, Limao
Other Authors: School of Civil and Environmental Engineering
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/164087
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1640872023-01-04T06:57:11Z Multi-objective optimization for cost-effective aseismic design of submerged floating tunnels considering weighted preferences He, Renfei Zhang, Limao School of Civil and Environmental Engineering Environmental Process Modelling Centre Nanyang Environment and Water Research Institute Engineering::Environmental engineering Submerged Floating Tunnel Multi-Objective Optimization In aseismic design of the submerged floating tunnel (SFT), both the seismic response and construction cost should be considered and optimized to achieve a balance between structural safety and project investment. To realize the simultaneous optimization of several design objectives, this study proposes a multi-objective-optimization-based framework for the cost-effective aseismic design of the SFT. Firstly, two design objectives, i.e., the transverse peak displacement (TPD) and the material cost (MC), are identified as the optimization objectives; The tube wall thickness, inclined angle of cables, and number of cable pairs are determined as the decision variables. Then the objective functions and constraint conditions are derived, and the nondominated sorting genetic algorithm-II (NSGA-II) is used to obtain the Pareto front and Pareto-optimal solution set. Considering the weighted preferences, a decision-making approach based on Tchebycheff's objective weight is developed to select the final optimal design scheme. The validity of the proposed approach is verified through a case study. The results imply that the optimal solution selected by the proposed approach is much superior in both TPD and MC compared with the original design scheme. Furthermore, compared with compromising programming, the proposed decision-making approach can emphasize more on TPD, which will gain more preferences from the designers. Nanyang Technological University The 1st author is grateful to Nanyang Technological University, Singapore for his Ph.D. research scholarship. 2023-01-04T06:57:11Z 2023-01-04T06:57:11Z 2022 Journal Article He, R. & Zhang, L. (2022). Multi-objective optimization for cost-effective aseismic design of submerged floating tunnels considering weighted preferences. Ocean Engineering, 250, 110976-. https://dx.doi.org/10.1016/j.oceaneng.2022.110976 0029-8018 https://hdl.handle.net/10356/164087 10.1016/j.oceaneng.2022.110976 2-s2.0-85126927934 250 110976 en Ocean Engineering © 2022 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Environmental engineering
Submerged Floating Tunnel
Multi-Objective Optimization
spellingShingle Engineering::Environmental engineering
Submerged Floating Tunnel
Multi-Objective Optimization
He, Renfei
Zhang, Limao
Multi-objective optimization for cost-effective aseismic design of submerged floating tunnels considering weighted preferences
description In aseismic design of the submerged floating tunnel (SFT), both the seismic response and construction cost should be considered and optimized to achieve a balance between structural safety and project investment. To realize the simultaneous optimization of several design objectives, this study proposes a multi-objective-optimization-based framework for the cost-effective aseismic design of the SFT. Firstly, two design objectives, i.e., the transverse peak displacement (TPD) and the material cost (MC), are identified as the optimization objectives; The tube wall thickness, inclined angle of cables, and number of cable pairs are determined as the decision variables. Then the objective functions and constraint conditions are derived, and the nondominated sorting genetic algorithm-II (NSGA-II) is used to obtain the Pareto front and Pareto-optimal solution set. Considering the weighted preferences, a decision-making approach based on Tchebycheff's objective weight is developed to select the final optimal design scheme. The validity of the proposed approach is verified through a case study. The results imply that the optimal solution selected by the proposed approach is much superior in both TPD and MC compared with the original design scheme. Furthermore, compared with compromising programming, the proposed decision-making approach can emphasize more on TPD, which will gain more preferences from the designers.
author2 School of Civil and Environmental Engineering
author_facet School of Civil and Environmental Engineering
He, Renfei
Zhang, Limao
format Article
author He, Renfei
Zhang, Limao
author_sort He, Renfei
title Multi-objective optimization for cost-effective aseismic design of submerged floating tunnels considering weighted preferences
title_short Multi-objective optimization for cost-effective aseismic design of submerged floating tunnels considering weighted preferences
title_full Multi-objective optimization for cost-effective aseismic design of submerged floating tunnels considering weighted preferences
title_fullStr Multi-objective optimization for cost-effective aseismic design of submerged floating tunnels considering weighted preferences
title_full_unstemmed Multi-objective optimization for cost-effective aseismic design of submerged floating tunnels considering weighted preferences
title_sort multi-objective optimization for cost-effective aseismic design of submerged floating tunnels considering weighted preferences
publishDate 2023
url https://hdl.handle.net/10356/164087
_version_ 1754611265082228736