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contributor authorHong-Nan Li
contributor authorYu-Jing Li
date accessioned2019-09-18T10:40:51Z
date available2019-09-18T10:40:51Z
date issued2019
identifier other%28ASCE%29EM.1943-7889.0001621.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4260204
description abstractTo estimate life-cycle cost and future seismic capacity, the life-cycle analysis in seismic design of bridges is formulated as an interactive multiobjective decision-making and optimization problem. Specifically, preference information based on engineering judgement and theoretical analysis is incorporated in the optimization procedure. The posteriori evolutionary multiobjective optimization (EMO) algorithm (nonpreference) and the preference-based interactive EMO algorithm are both applied to the seismic design of an reinforced concrete (RC) pier with two, three, and four objectives, namely, flexural strength coefficient, shear strength coefficient, reliability index of drift, and life-cycle cost coefficient. In terms of a rational displacement ductility, the safety preference information is applied to establish a value function after every few optimization runs, progressively directing the search of the EMO algorithm to more preferred solutions. By comparing the results of both algorithms, it is found that when there are more than three objectives, it is difficult for the nonpreference optimization to converge with the global Pareto frontier, resulting in a local optimal solution as the final design. The combination of preference structure and multiobjective optimization effectively avoids the challenges of global search and purposefully converges with the most preferred design.
publisherAmerican Society of Civil Engineers
titleInteractive Multiobjective Optimization for Life-Cycle Analysis in Seismic Design of Bridges
typeJournal Paper
journal volume145
journal issue7
journal titleJournal of Engineering Mechanics
identifier doi10.1061/(ASCE)EM.1943-7889.0001621
page04019050
treeJournal of Engineering Mechanics:;2019:;Volume ( 145 ):;issue: 007
contenttypeFulltext


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