Benchmarking dataset for multiskilled workforce planning with uncertain demand

This dataset is related with the Data Article entitled: “A benchmark dataset for the retail multiskilled personnel planning under uncertain demand”, which was submitted to Data Science Journal. This data article describes datasets from a home improvement retail store located in Santiago, Chile. The datasets have been developed to solve a multiskilled personnel assignment problem (MPAP) under uncertain demand. Particularly, this database is related to the published article "Multiskilled personnel assignment problem under uncertain demand: A benchmarking analysis" developed by Henao et al. (2022).

The datasets contain real and simulated data. Regarding the real dataset, it includes information about the store size, number of employees, employment-contract characteristics, mean value of weekly hours demand in each department, and cost parameters. Regarding the simulated datasets, they include information about the random parameter of weekly hours demand in each store department. The simulated data are presented in 18 text files classified by: (i) Sample type (in-sample or out-of-sample). (ii) Truncation-type method (zero-truncated or percentile-truncated). (iii) Coefficient of variation (5, 10, 20, 30, 40, 50%).