Paper on strategic workforce planning with DRL at LOD


A paper on Deep Reinforcement Learning (DRL) for strategic workforce planning co-authored with Yannick Smit, Sandjai Bhulai and Ehsan Mehdad is accepted as a long paper at the LOD conference.

In this paper, we model strategic workforce planning as a stochastic nonlinear optimization problem, learn a generative model from data and use it as a simulator in a simulation-optimization approach.

We show that the DRL approach enables optimizing an organizations' strategic workforce goals directly. It significantly outperforms the strong baseline (linear programming) on a strategic objective while closely approaching it on an operational objective.

Details and preprint will follow.

Update 2022-07-04 Preprint is now available!

Update 2023-03-10 Paper is now available in Springer LNCS!