文章基本信息

标题：Stochastic quality-cost optimization system hybridizing multi-objective genetic algorithm and quality function deployment
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作者：Tae-Kyung Lim ; Won-Suk Jang ; Jae-Ho Choi 等
期刊名称：Journal of Civil Engineering and Management
印刷版ISSN：1392-3730
出版年度：2015
卷号：21
期号：4
DOI：10.3846/13923730.2014.890647
语种：English
出版社：Vilnius Gediminas Technical University
摘要：This paper introduces an automated tool, the stochastic quality-cost optimization (SQCO) system, that hybridizes multi-objective genetic algorithm (MOGA) and Quality Function Deployment (QFD). The system identifies the optimal trade-off between a construction owner’s satisfaction and a contractor’s satisfaction. It is important to reconcile the project participants’ conflicting interests because the construction owner aims to maximize the quality of construction while the contractor aims to minimize the cost of construction. MOGA is used to optimize resource allocation when owner satisfaction and contractor satisfaction are pursued at the same time under a limited budget. Multi-objective optimization is integrated with simulation to effectively deal with the uncertainties of the QFD input and the variability of the QFD output. This study is of value to practitioners because SQCO allows for the establishment of a quality plan that satisfies all of the multi project participants. The study is also of relevance to researchers in that it allows researchers to expeditiously identify an optimal design alternative of construction methods and operations. A test case implemented with a curtain-wall unit verifies the usability and validity of the system in practice.