Research on optimisation method for project site selection based on improved genetic algorithm

Ling-min Yang, Zhong-min Tang and Si-jun Liu

International Journal of Industrial and Systems Engineering, 2022, vol. 40, issue 3, 309-324

Abstract: In order to overcome the problems of low correlation between location impact index and target project, and low customer satisfaction in current research methods of project location, an optimisation method of project location based on improved genetic algorithm is proposed and designed. Collect the data needed for project site selection and integrate relevant data efficiently, and build the framework structure of project site selection. According to the evaluation index of project location, the existing genetic algorithm is improved. The improved genetic algorithm is applied to the optimisation of project location, and the eigenvalues and correlation factors of project location are optimised to realise the optimisation of project location. The experimental results show that the fit degree between the proposed method and the target project is between 0.9-1.0, and the user satisfaction is between 95%-99%, which proves that the proposed method has good robustness.

Keywords: improving genetic algorithm; project location; optimising method. (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:40:y:2022:i:3:p:309-324

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