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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, p. 41-52Article 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, p. 41-52
Keywords [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; Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-10629DOI: 10.5121/ijaia.2015.6103OAI: oai:DiVA.org:his-10629DiVA, id: diva2:785072
Funder
Knowledge FoundationAvailable from: 2015-02-02 Created: 2015-02-02 Last updated: 2018-03-29Bibliographically approved

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Syberfeldt, AnnaAndersson, MartinNg, Amos

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