Determining the number of new employees with learning, forgetting and variable wage with a newsvendor model in pull systems

Yufei Huang (1, 2) , Feng Chu (3) , Chengbin Chu (4) , Yingluo Wang (1)

1 School of Management
2 LOSI - Laboratoire d'Optimisation des Systèmes Industriels
3 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
4 LGI - Laboratoire Génie Industriel - EA 2606

This paper develops a new quantitative model to find the optimal number of new employees with a Newsvendor model in a pull production system. This model allows learning, forgetting and variable wage. This paper also provides numerical results on sensitivity analysis, and compares the numerical results in three different situations: the situation with both learning and forgetting effect, that with learning effect but without forgetting effect and the situation with neither learning nor forgetting effect. The conclusions drawn from the comparison may offer theoretical insight for human resource managers to make appropriate employment decisions.

Domains: Computer Science [cs]; Operations Research [cs.RO]

Yufei Huang, Feng Chu, Chengbin Chu, Yingluo Wang. Determining the number of new employees with learning, forgetting and variable wage with a newsvendor model in pull systems. Journal of Intelligent Manufacturing, 2012, 23 (1), pp.73-89. ⟨10.1007/s10845-009-0307-5⟩. ⟨hal-00735059⟩