Database for a multiskilled personnel assignment problem under uncertain demand
This repository 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 datasbase is related to the article "Multiskilled personnel assignment problem under uncertain demand: A benchmarking analysis" developed by Henao et al. (2021). 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 (percentile-truncated or zero-truncated). (iii) Coefficient of variation (5, 10, 20, 30, 40, 50%).