Construction of human resource allocation model of flow production line based on fuzzy mathematics

Chengye Zhang

International Journal of Manufacturing Technology and Management, 2023, vol. 37, issue 3/4, 362-375

Abstract: In order to improve the rationality and access rate of human resource allocation, a method of constructing human resource allocation model of assembly line based on fuzzy mathematics is proposed. Firstly, human resource data is encrypted through chaotic sequence. Then, the talent flow of assembly line is regarded as a random variable, and a Markov prediction model is established to reduce the prediction error combined with constraints. Finally, the fuzzy mathematical algorithm is introduced to divide the importance degree of posts, establish the human resource allocation model, and realise the human resource allocation of assembly line. Verification shows that the maximum matching degree of the method is 1.90, and the access rate is less than 2 s, which effectively improves the matching degree and reduces the access time.

Keywords: fuzzy mathematics; human resource allocation; prediction model; chaotic sequence; Markov. (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=133476 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmtma:v:37:y:2023:i:3/4:p:362-375

Access Statistics for this article

More articles in International Journal of Manufacturing Technology and Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().