A Study of Construction Quality Audit Project Selection and Auditor Assignment Using Genetic Algorithm

• Main Authors: Hsiang-Lin Kung, 孔祥林
• Other Authors: Yu-Ren Wang
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/85606835955336678727

碩士 === 國立高雄應用科技大學 === 土木工程與防災科技研究所 === 97 === Construction quality audit is the third level quality control procedures enforced by the Public Construction Commission of the Executive Yuan. In so doing, auditors are able to examine the quality and progress objectively as a third party. In practice, the audited projects are first selected by the audit project team and then auditors are invited according to their background and expertise. This project and auditor selection process is normally carried out based on personal experience and the quality of the selection outcome is hard to predict and control. In fact, it is a difficult job assignment task for the audit project team to select appropriate projects and their auditors because there are normally many projects and auditors to choose from. The purpose of this research is to establish a decision support system which will recommend appropriate audit projects and their associated auditors when relevant regulations and limitations are under consideration. The decision support system consists of a Genetic Algorithm model to solve the multi-objective job assignment problem. The prime objective of the GA model is to find the best match between the projects and auditors based on project characteristics and auditor expertise. Information provided by the Kaohsiung County Government Project Audit Team is used to build and test the model. Finally, the model results from real data input are compared with existing human selection results. It is found that the mode proposed by this research is able to produce a “much better match” between projects and auditors in a timely fashion. It is suggested that this model to be utilized by the project audit team to assist with the audit projects and auditors selection process.