Applying genetic algorithms for construction quality auditor assignment in public construction projects

摘要

Random third party quality audits are mandatory by the regulations for public construction projects in Tai-wan. 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. This is a difficult work assignment problem because there are normally hundreds of projects and dozens of auditors to choose from. The purpose of this research is to establish a genetic algorithm-based model to assist with the project selection and auditor as-signment process. The model is set up to find the optimal match between the project characteristics and au-ditor expertise from approximately 5.09E + 29 possible combinations. Information provided by the Kaohsiung County Government is used to validate the model. The results show that the model is not only valid but also able to produce a "much better match" between projects and auditors when comparing to man-ual assignment.