Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Multi-Objective Evolutionary Optimization of Personnel Scheduling
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0003-3973-3394
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0003-0111-1776
PostNord AB, Solna, Sweden .
2015 (English)In: International Journal of Artificial Intelligence & Applications, ISSN 0976-2191, E-ISSN 0975-900X, Vol. 6, no 1, 41-52 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents an evolutionary multi-objective simulation-optimization system for personnelscheduling. The system is developed for the Swedish postal services and aims at finding personnelschedules that minimizes both total man hours and the administrative burden of the person responsible forhandling schedules. For the optimization, the multi-objective evolutionary algorithm NSGA-II isimplemented. In order to make the optimization fast enough, a two-level parallelisation model is beingadopted. The simulation-optimization system is evaluated on a real-world test case and results from theevaluation shows that the algorithm is successful in optimizing the problem.

Place, publisher, year, edition, pages
AIRCC Publishing Corporation , 2015. Vol. 6, no 1, 41-52 p.
Keyword [en]
Multi-objective evolutionary optimization, NSGA-II, hill climbing, personnel scheduling, case study.
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-10629DOI: 10.5121/ijaia.2015.6103OAI: oai:DiVA.org:his-10629DiVA: diva2:785072
Funder
Knowledge Foundation
Available from: 2015-02-02 Created: 2015-02-02 Last updated: 2017-12-05Bibliographically approved

Open Access in DiVA

fulltext(517 kB)596 downloads
File information
File name FULLTEXT01.pdfFile size 517 kBChecksum SHA-512
5443c8d3b45cbc3ff5dbc6368f7396d51ee64f0a6bda0ce3c451a16f93d65bcca43dd1550889ecbba05fcd16fbfc8994b6c18dba6ce21d3b6028f954a2261e68
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Syberfeldt, AnnaAndersson, MartinNg, Amos
By organisation
School of Engineering ScienceThe Virtual Systems Research Centre
In the same journal
International Journal of Artificial Intelligence & Applications
Production Engineering, Human Work Science and Ergonomics

Search outside of DiVA

GoogleGoogle Scholar
Total: 596 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 2042 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf