东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2008, Vol. 29 ›› Issue (1): 125-129.DOI: -

• 论著 • 上一篇    下一篇

基于小生境Pareto遗传算法的混凝土桥面板维修优化

边晶梅;朱浮声;陈耕野;白泉;   

  1. 东北大学资源与土木工程学院;东北大学资源与土木工程学院;东北大学资源与土木工程学院;东北大学资源与土木工程学院 辽宁沈阳110004;辽宁沈阳110004;沈阳建筑大学土木工程学院;辽宁沈阳110068;辽宁沈阳110004;辽宁沈阳110004
  • 收稿日期:2013-06-22 修回日期:2013-06-22 出版日期:2008-01-15 发布日期:2013-06-22
  • 通讯作者: Bian, J.-M.
  • 作者简介:-
  • 基金资助:
    辽宁省交通科技重点项目(0512)

Maintenance optimization of concrete bridge deck using the niched Pareto genetic algorithm

Bian, Jing-Mei (1); Zhu, Fu-Sheng (1); Chen, Geng-Ye (1); Bai, Quan (1)   

  1. (1) School of Resources and Civil Engineering, Northeastern University, Shenyang 110004, China; (2) School of Civil Engineering, Shenyang Jianzhu University, Shenyang 110068, China
  • Received:2013-06-22 Revised:2013-06-22 Online:2008-01-15 Published:2013-06-22
  • Contact: Bian, J.-M.
  • About author:-
  • Supported by:
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摘要： 混凝土桥面板是桥梁组成部分中最易损坏的结构单元,维修频率最高.研究了在各种约束条件下如何得到混凝土桥面板最佳维修策略问题.建立了桥面板维修的多目标优化模型,同时满足费用最小化以及性能最大化等多个相互冲突的目标,并采用小生境Pareto遗传算法(NPGA)求解.结果表明,基于NPGA的桥面板维修优化方法提供了一系列可行解供桥梁管理者根据偏好进行挑选,增加了维修策略的选择范围.这种方法既可以避免单目标优化无法考虑其他影响因素的缺点,又可以克服多目标优化传统解法的某些不足,提高了维修决策的科学性、合理性,适于指导桥梁维修工程实践.

关键词: 桥梁管理, 维修策略, 混凝土桥面板, 多目标优化, 遗传算法, NPGA

Abstract: As the most damageable component of bridge, the concrete bridge deck is most required to maintain. The problem of obtaining the optimal maintenance strategy of concrete bridge deck under limited resources restriction is investigated. A multiobjective optimization model of concrete bridge deck is therefore developed for several objectives which conflict with each other, such as minimizing the total cost but maximizing the performance simultaneously, and the niched Pareto genetic algorithm (NPGA) is introduced to solve the model. The multiobjective optimization of bridge deck maintenance based on NPGA provides bridge managers with a set of feasible solutions for selection in accordance to their own preference, by which not only the disadvantage of single objective optimization without other influencing factors taken into account can be avoided but also some defects can be overcome in conventional solutions to the problem of multiobjective optimization. In this way the maintenance decision will be made more scientific and rational so as to make the maintenance for existing bridges proper.

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