Citation
A list-scheduling approach for the planning of assessment centers. In proceedings of the 7th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2015), 25 - 28 Aug 2015, Prague, Czech Republic, pages 541-554, 2015.
Paper
Abstract
Many companies run assessment centers in order to select candidates for open job positions. During an assessment center, each candidate performs a set of exercises; thereby, the candidates are evaluated by so-called assessors. Additional constraints such as preparation and evaluation times, participation of actors in the exercises, no-go constraints, and time windows for lunch breaks contribute to the complexity of planning such assessment centers. We propose a list-scheduling approach to solve this planning problem heuristically; to this end, we develop novel procedures for devising an appropriate scheduling list and for generating a feasible schedule. In an experimental performance analysis, we applied this approach to a set of problem instances that represent or are devised from real cases. It turns out that the approach generates optimal or near-optimal schedules within relatively short CPU times.
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Bibtex
@INPROCEEDINGS{2015-541-554-P, author = {A. Zimmermann and N. Trautmann},
title = {A list-scheduling approach for the planning of assessment centers},
booktitle = {In proceedings of the 7th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2015), 25 - 28 Aug 2015, Prague, Czech Republic},
year = {2015},
editor = {Z. Hanzalek and G. Kendall and B. McCollum and P. Sucha},
pages = {541--554},
note = {Paper},
abstract = { Many companies run assessment centers in order to select candidates for open job positions. During an assessment center, each candidate performs a set of exercises; thereby, the candidates are evaluated by so-called assessors. Additional constraints such as preparation and evaluation times, participation of actors in the exercises, no-go constraints, and time windows for lunch breaks contribute to the complexity of planning such assessment centers. We propose a list-scheduling approach to solve this planning problem heuristically; to this end, we develop novel procedures for devising an appropriate scheduling list and for generating a feasible schedule. In an experimental performance analysis, we applied this approach to a set of problem instances that represent or are devised from real cases. It turns out that the approach generates optimal or near-optimal schedules within relatively short CPU times.},
owner = {Graham},
timestamp = {2017.01.16},
webpdf = {2015-541-554-P.pdf} }