Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/164087
Title: Multi-objective optimization for cost-effective aseismic design of submerged floating tunnels considering weighted preferences
Authors: He, Renfei
Zhang, Limao
Keywords: Engineering::Environmental engineering
Issue Date: 2022
Source: 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
Journal: Ocean Engineering
Abstract: 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.
URI: https://hdl.handle.net/10356/164087
ISSN: 0029-8018
DOI: 10.1016/j.oceaneng.2022.110976
Schools: School of Civil and Environmental Engineering 
Research Centres: Environmental Process Modelling Centre 
Nanyang Environment and Water Research Institute 
Rights: © 2022 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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