Work Assignment Optimization Using Genetic Algorithms

Abstract:

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Random third party quality audits are mandatory by the regulations for public construction projects in Taiwan. This project and auditor selection process 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 assignment process. The model is set up to find the optimal match between the project characteristics and auditor expertise from approximately 5.09E+29 possible combinations. Information provided by the Kaohsiung County Government is used to test 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 manual assignment.

Info:

Periodical:

Edited by:

Daizhong Su, Qingbin Zhang and Shifan Zhu

Pages:

526-529

DOI:

10.4028/www.scientific.net/KEM.450.526

Citation:

Y. R. Wang et al., "Work Assignment Optimization Using Genetic Algorithms", Key Engineering Materials, Vol. 450, pp. 526-529, 2011

Online since:

November 2010

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Price:

$35.00

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