A benchmark dataset for the retail multiskilled personnel planning under uncertain demand

This dataset is related with the Data in Brief article entitled: “A benchmark dataset for the retail multiskilled personnel planning under uncertain demand”, which was submitted to Data in Brief 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%).

本数据集与发表在《Data in Brief》期刊上的文章《A benchmark dataset for the retail multiskilled personnel planning under uncertain demand》相关，该文章已被投稿至该期刊。该数据文章描述了位于智利圣地亚哥的一家家居装修零售商店的数据集。这些数据集旨在解决不确定需求下的多技能人员分配问题（MPAP）。特别是，此数据库与 Henao 等人（2022年）开发的已发表文章《Multiskilled personnel assignment problem under uncertain demand: A benchmarking analysis》相关联。数据集包含真实和模拟数据。就真实数据集而言，它包括关于店铺规模、员工数量、雇佣合同特征、每个部门的每周小时需求均值以及成本参数的信息。就模拟数据集而言，它们包括关于每个商店部门的每周小时需求随机参数的信息。模拟数据以18个文本文件呈现，并根据以下类别进行分类：（i）样本类型（样本内或样本外）。（ii）截断类型方法（零截断或百分位截断）。（iii）变异系数（5%，10%，20%，30%，40%，50%）。