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

Tracking #: 797-1777


César Augusto HenaoORCID logo https://orcid.org/0000-0001-8253-5794
Andrés Felipe PortoORCID logo https://orcid.org/0000-0003-1110-1547
Virginia I. GonzálezORCID logo https://orcid.org/0000-0003-3676-4865

Responsible editor: 

Tobias Kuhn

Submission Type: 

Resource Paper


In this data article, we present and describe datasets designed to address multiskilled personnel assignment problems (MPAP) under uncertain demand. The data article introduces simulated datasets and a real dataset obtained from a retail store in Chile. The real dataset provides details on the structure of the store, including the number of departments and workers, the type of labor contract, the cost parameter values, and the average demand across all store departments. The simulated datasets, consisting of 18 categorized text files, were generated through Monte Carlo simulation to encapsulate information about the stochastic demand for store departments. These text files are classified based on: (i) type of sample (in-sample or out-of-sample), (ii) type of truncation method (zero-truncated or percentile-truncated), and (iii) demand coefficient of variation (5%, 10%, 20%, 30%, 40%, 50%). This categorization allows academics and practitioners to select the scenarios that meet with their specific research or application needs, increasing the flexibility and applicability of the datasets. In addition, researchers and practitioners can use these comprehensive real and simulated datasets to benchmark the performance of diverse optimization methods under uncertain demand, thereby ensuring robust multiskilling levels for similar MPAPs. Furthermore, we offer an Excel workbook with the capability to generate up to 10,000 demand scenarios for varying coefficients of variation in demand.


Supplementary Files (optional): 

Previous Version: 


  • Reviewed

Data repository URLs: 

Date of Submission: 

Friday, January 26, 2024

Date of Decision: 

Friday, February 16, 2024

Nanopublication URLs:



Solicited Reviews:


Response to the editor and the reviewers

Dear Tobias Kuhn, editors-in-chief and reviewers,


Thank you for your feedback on our manuscript entitled "A benchmark dataset for retail multiskilled personnel planning under uncertain demand" (#797-1777). Based on the instructions provided, we have uploaded three documents: (i) a revised version of the manuscript in Pdf and Word files, (ii) all image files needed to produce the final paper, and (iii) a document containing the responses to the reviewers.


We have addressed the reviewer's comment by expanding the discussion of related work in the new version of the manuscript. Most importantly, we have added Subsection 2.1, which identifies a set of research articles that addressed PSPs with applications in industries other than retail, sometimes considering multiskilled workers and sometimes not. The list of articles is particularly valuable as all the articles listed in Table 1 are characterized by having an associated data repository with public access, thus providing valuable datasets for researchers or practitioners to conduct experiments and/or benchmarking.


We believe that this new subsection strengthens and expands the contribution of our data article by providing readers with a compilation of datasets that have already been published by other authors and can be used for experimentation or benchmarking in case studies other than retail.


Please let us know if there are any additional requirements.


Best regards,


César A. Henao