Workforce scheduling and routing problems: literature survey and computational study

Castillo-Salazar, J. Arturo and Landa-Silva, Dario and Qu, Rong (2016) Workforce scheduling and routing problems: literature survey and computational study. Annals of Operations Research, 239 (1). pp. 39-67. ISSN 1572-9338

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview

Abstract

In the context of workforce scheduling, there are many scenarios in which personnel must carry out tasks at different locations hence requiring some form of transportation. Examples of these type of scenarios include nurses visiting patients at home, technicians carrying out repairs at customers’ locations and security guards performing rounds at different premises, etc. We refer to these scenarios as workforce scheduling and routing problems (WSRP) as they usually involve the scheduling of personnel combined with some form of routing in order to ensure that employees arrive on time at the locations where tasks need to be performed. The first part of this paper presents a survey which attempts to identify the common features of WSRP scenarios and the solution methods applied when tackling these problems. The second part of the paper presents a study on the computational difficulty of solving these type of problems. For this, five data sets are gathered from the literature and some adaptations are made in order to incorporate the key features that our survey identifies as commonly arising in WSRP scenarios. The computational study provides an insight into the structure of the adapted test instances, an insight into the effect that problem features have when solving the instances using mathematical programming, and some benchmark computation times using the Gurobi solver running on a standard personal computer.

Item Type: Article
Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-014-1687-2
Schools/Departments: University of Nottingham UK Campus > Faculty of Science > School of Computer Science
Identification Number: https://doi.org/10.1007/s10479-014-1687-2
Depositing User: Qu, Rong
Date Deposited: 10 Jun 2016 08:39
Last Modified: 18 Sep 2016 05:09
URI: http://eprints.nottingham.ac.uk/id/eprint/33874

Actions (Archive Staff Only)

Edit View Edit View