Research Article
A Bilateral Matching Management Method for Intelligent Workgroups Considering the Balance of Personnel and Positions
@INPROCEEDINGS{10.4108/eai.8-12-2023.2344477, author={Feng Liu and Weixi Lv and Dinan Jiang and Lvgang Fan and Ting Wang}, title={A Bilateral Matching Management Method for Intelligent Workgroups Considering the Balance of Personnel and Positions}, proceedings={Proceedings of the 5th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2023, December 8--10, 2023, Guangzhou, China}, publisher={EAI}, proceedings_a={MSIEID}, year={2024}, month={4}, keywords={bilateral matching; person-post management; preference order; multi-objective optimization; improved nsga-ii algorithm}, doi={10.4108/eai.8-12-2023.2344477} }- Feng Liu
Weixi Lv
Dinan Jiang
Lvgang Fan
Ting Wang
Year: 2024
A Bilateral Matching Management Method for Intelligent Workgroups Considering the Balance of Personnel and Positions
MSIEID
EAI
DOI: 10.4108/eai.8-12-2023.2344477
Abstract
In order to solve the bilateral matching problem of digital person-post in the intelligent team, a bilateral matching model between personnel and positions considering the balance of overall and individual satisfaction has been proposed. Firstly, the preference order of employees and posts is calculated based on the principle of object element through the mutual evaluation between employees and posts. From the perspective of both enterprises and employees, considering the individual differences in satisfaction among employees. The optimization objective is to maximize the overall satisfaction and minimize the variance of individual satisfaction, the constraints are the maximum number of individual matches and the worst match limit. Following that, the NSGA-II algorithm is applied to solve the problem, and the chromosome is coded in two-dimensional 0-1. The Pareto front solution set of (0.24,0.28) is taken as the example of the shift management platform information of a company in the State Grid, and it is verified that the matching solution satisfying the overall and individual satisfaction balance can be obtained by the method of this paper. The matching model of this paper is implemented in the digital job matching function of the platform, which can provide the job manager with a matching solution that satisfies both sides.