Dataset for solving a hybrid flexibility strategy on personnel scheduling problem in the retail industry

Andrés Felipe Porto, César Augusto Henao*, Héctor López-Ospina, Esneyder Rafael González, Virginia I. González

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

This data article describes datasets from a home improvement retail store located in Santiago, Chile. The datasets have been developed to simultaneously solve a staffing and tour scheduling problem that incorporates flexible contracts and multiskilled staff. This Data in Brief article is related to the published article “Hybrid flexibility strategy on personnel scheduling: Retail case study” [1]. The datasets contain real, processed, and simulated data. Regarding the real and processed datasets, they are presented for three different store sizes (4, 5 or 6 departments). Real datasets include information about the employment-contract characteristics, cost parameters, and a forecast of the number of employees required in each department for each day of the week and each time period into which the operating day is divided. As regards the data processed for the case study, they include the set of skill sets considering that the employees can be trained in a maximum of two store departments. Regarding the simulated datasets, they include information about the random parameter of staff demand in each store department. The simulated data are presented in 90 text files classified by: (i) Store size (4, 5 or 6 departments). (ii) Coefficient of variation (10, 20, 30%). (iii) Instance identification number (10 instances per scenario that resulted from combining the store sizes and coefficients of variation). Researchers can use the datasets for benchmarking the performance of different approaches with the one presented by Porto et al. [1], and in consequence, they can find solutions to the same (or similar) type of personnel scheduling problem. The dataset includes an Excel workbook that can be used to randomly generate staff demand instances according to a chosen coefficient of variation.

Original languageEnglish
Article number106066
JournalData in Brief
Volume32
DOIs
StatePublished - Oct 2020
Externally publishedYes

Bibliographical note

Funding Information:
This research was supported by “Fundación para la Promoción de la Investigación y la Tecnología (FPIT)” under Grants 4.254 and 4.523 and Universidad del Norte under Grant 2017–13. Finally, the authors would like to thank their colleagues at SHIFT SpA for providing the real data from our case study.

Publisher Copyright:
© 2020 The Authors

Keywords

  • Flexible contracts
  • Multiskilling
  • Personnel scheduling
  • Retail services
  • Staffing
  • Tour scheduling
  • Workforce flexibility

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