The University of Southampton
University of Southampton Institutional Repository

Iterated local search for workforce scheduling and routing problems

Iterated local search for workforce scheduling and routing problems
Iterated local search for workforce scheduling and routing problems
The integration of scheduling workers to perform tasks with the traditional vehicle routing problem gives rise to the workforce scheduling and routing problems (WSRP). In the WSRP, a number of service technicians with different skills, and tasks at different locations with pre-defined time windows and skill requirements are given. It is required to find an assignment and ordering of technicians to tasks, where each task is performed within its time window by a technician with the required skill, for which the total cost of the routing is minimized. This paper describes an iterated local search (ILS) algorithm for the WSRP. The performance of the proposed algorithm is evaluated on benchmark instances against an off-the-shelf optimizer and an existing adaptive large neighbourhood search algorithm. The proposed ILS algorithm is also applied to solve the skill vehicle routing problem, which can be viewed as a special case of the WSRP. The computational results indicate that the proposed algorithm can produce high-quality solutions in short computation times.
1381-1231
471-500
Bektas, Tolga
0db10084-e51c-41e5-a3c6-417e0d08dac9
Xie, Fulin
8ab88939-a499-4a79-b7fb-f533033212f5
Potts, Christopher
58c36fe5-3bcb-4320-a018-509844d4ccff
Bektas, Tolga
0db10084-e51c-41e5-a3c6-417e0d08dac9
Xie, Fulin
8ab88939-a499-4a79-b7fb-f533033212f5
Potts, Christopher
58c36fe5-3bcb-4320-a018-509844d4ccff

Bektas, Tolga, Xie, Fulin and Potts, Christopher (2017) Iterated local search for workforce scheduling and routing problems. Journal of Heuristics, 23 (6), 471-500. (doi:10.1007/s10732-017-9347-8).

Record type: Article

Abstract

The integration of scheduling workers to perform tasks with the traditional vehicle routing problem gives rise to the workforce scheduling and routing problems (WSRP). In the WSRP, a number of service technicians with different skills, and tasks at different locations with pre-defined time windows and skill requirements are given. It is required to find an assignment and ordering of technicians to tasks, where each task is performed within its time window by a technician with the required skill, for which the total cost of the routing is minimized. This paper describes an iterated local search (ILS) algorithm for the WSRP. The performance of the proposed algorithm is evaluated on benchmark instances against an off-the-shelf optimizer and an existing adaptive large neighbourhood search algorithm. The proposed ILS algorithm is also applied to solve the skill vehicle routing problem, which can be viewed as a special case of the WSRP. The computational results indicate that the proposed algorithm can produce high-quality solutions in short computation times.

Text
ILS Paper - Accepted Manuscript
Download (196kB)
Text
s10732-017-9347-8 - Version of Record
Available under License Creative Commons Attribution.
Download (523kB)

More information

Accepted/In Press date: 26 June 2017
e-pub ahead of print date: 18 July 2017
Published date: December 2017

Identifiers

Local EPrints ID: 412183
URI: https://eprints.soton.ac.uk/id/eprint/412183
ISSN: 1381-1231
PURE UUID: 92c7b77b-187c-41a9-bd7a-20076ddcc37e
ORCID for Tolga Bektas: ORCID iD orcid.org/0000-0003-0634-144X

Catalogue record

Date deposited: 13 Jul 2017 16:31
Last modified: 15 Aug 2019 04:45

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×