DocumentCode :
2573449
Title :
Quality Reliability-Cost Optimization of Construction Project Based on Genetic Algorithm
Author :
Yu-fang Shi ; Hui-min Li ; Ning Lu
Author_Institution :
Sch. of Civil Eng., Xi´an Univ. of Arch. & Tech., Xi´an, China
fYear :
2009
fDate :
2-3 May 2009
Firstpage :
159
Lastpage :
162
Abstract :
Construction project is regarded as a complex network system in which quality reliability is an important index to express quality grade, so quality -cost Optimization is one of the most crucial aspects of construction project planning, which in fact is a multi objective optimization problem. A mathematical model is established and an evolutionary algorithm genetic algorithm (GA) was employed to solve the quality reliability-cost optimization problem. In the application of GA, penalty function is used to handle the constraint. In the selection strategy of GA, Sorting on the evaluation function and optimal conservation strategy are adopted which improve the convergence performance of GA. Finally, a test example is given to verify the advantage of the new method which combines quality reliability with cost in the construction which is benefit for the cost optimization research.
Keywords :
construction industry; genetic algorithms; planning; quality management; reliability; complex network system; construction project; evaluation function; evolutionary algorithm; genetic algorithm; mathematical model; multi objective optimization problem; optimal conservation strategy; penalty function; project planning; quality reliability-cost optimization; Complex networks; Convergence; Cost function; Evolution (biology); Genetic algorithms; Genetic engineering; Optimization methods; Project management; Reliability engineering; Sorting; Genetic Algorithm; quality -cost Optimization; quality reliability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering Computation, 2009. ICEC '09. International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-0-7695-3655-2
Type :
conf
DOI :
10.1109/ICEC.2009.32
Filename :
5167115
Link To Document :
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