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%).

本数据集关联于一篇已提交至《数据简报（Data in Brief）》期刊、题为《不确定需求下零售多技能人员规划基准数据集》的研究短文。该数据短文介绍了智利圣地亚哥一家家居零售门店的相关数据集，旨在解决不确定需求下的多技能人员分配问题（Multiskilled Personnel Assignment Problem, MPAP）。具体而言，本数据集关联于Henao等人（2022）发表的题为《不确定需求下的多技能人员分配问题：基准分析》的研究论文。

本数据集包含真实数据与模拟数据两类。其中，真实数据集涵盖门店规模、员工数量、雇佣合同特征、各部门周工时需求均值以及成本参数等信息；模拟数据集则包含各门店部门周工时需求的随机参数相关信息。模拟数据以18个文本文件形式提供，分类依据如下：(i) 样本类型（样本内或样本外）；(ii) 截断方法（零截断或百分位数截断）；(iii) 变异系数（5%、10%、20%、30%、40%、50%）。