Multiobjective Optimization of Bridge Deck Rehabilitation Using a Genetic Algorithm

The solution methods of multiobjective optimization have undergone constant development over the past three decades. However, the methods available to date are not particularly robust. Because of the complicated relationship between the rehabilitation cost and deterioration degree of infrastructure...

Full description

Saved in:
Bibliographic Details
Published inComputer-aided civil and infrastructure engineering Vol. 12; no. 6; pp. 431 - 443
Main Authors Liu, Chunlu, Hammad, Amin, Itoh, Yoshito
Format Journal Article
LanguageEnglish
Published Boston, USA and Oxford, UK Blackwell Publishers Inc 01.11.1997
Online AccessGet full text

Cover

Loading…
More Information
Summary:The solution methods of multiobjective optimization have undergone constant development over the past three decades. However, the methods available to date are not particularly robust. Because of the complicated relationship between the rehabilitation cost and deterioration degree of infrastructure systems, it is difficult to find a near‐optimal solution using common optimization methods. Since genetic algorithms work with a population of points, they can capture a number of solutions simultaneously and easily incorporate the concept of Pareto optimality. In this paper a simple genetic algorithm with two additional techniques, Pareto optimality ranking and fitness sharing, is implemented for the deck rehabilitation plan of network‐level bridges, aiming to minimize the total rehabilitation cost and deterioration degree. This approach is illustrated by a simple example and then applied to a practical bridge system with a large number of bridges.
Bibliography:ark:/67375/WNG-76R041TV-M
ArticleID:MICE075
istex:82E3E199BA802D7B95D19E8CC2C6D80803B036E7
ISSN:1093-9687
1467-8667
DOI:10.1111/0885-9507.00075