France Telecom workforce scheduling problem: a challenge

Sebastian Pokutta; Gautier Stauffer

RAIRO - Operations Research (2009)

  • Volume: 43, Issue: 4, page 375-386
  • ISSN: 0399-0559

Abstract

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In this paper, we describe the methodology used to tackle France Telecom workforce scheduling problem (the subject of the Roadef Challenge 2007) and we report the results obtained on the different data sets provided for the competition. Since the problem at hand appears to be NP-hard and due to the high dimensions of the instance sets, we use a two-step heuristical approach. We first devise a problem-tailored heuristic that provides good feasible solutions and then we use a meta-heuristic scheme to improve the current results. The tailored heuristic makes use of sophisticated integer programming models and the corresponding sub-problems are solved using CPLEX while the meta-heuristic framework is a randomized local search algorithm. The approach herein described allowed us to rank 5th in this challenge.

How to cite

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Pokutta, Sebastian, and Stauffer, Gautier. "France Telecom workforce scheduling problem: a challenge." RAIRO - Operations Research 43.4 (2009): 375-386. <http://eudml.org/doc/250548>.

@article{Pokutta2009,
abstract = { In this paper, we describe the methodology used to tackle France Telecom workforce scheduling problem (the subject of the Roadef Challenge 2007) and we report the results obtained on the different data sets provided for the competition. Since the problem at hand appears to be NP-hard and due to the high dimensions of the instance sets, we use a two-step heuristical approach. We first devise a problem-tailored heuristic that provides good feasible solutions and then we use a meta-heuristic scheme to improve the current results. The tailored heuristic makes use of sophisticated integer programming models and the corresponding sub-problems are solved using CPLEX while the meta-heuristic framework is a randomized local search algorithm. The approach herein described allowed us to rank 5th in this challenge. },
author = {Pokutta, Sebastian, Stauffer, Gautier},
journal = {RAIRO - Operations Research},
keywords = {Workforce scheduling; schedule generation scheme; roadef challenge.; workforce scheduling; roadef challenge},
language = {eng},
month = {10},
number = {4},
pages = {375-386},
publisher = {EDP Sciences},
title = {France Telecom workforce scheduling problem: a challenge},
url = {http://eudml.org/doc/250548},
volume = {43},
year = {2009},
}

TY - JOUR
AU - Pokutta, Sebastian
AU - Stauffer, Gautier
TI - France Telecom workforce scheduling problem: a challenge
JO - RAIRO - Operations Research
DA - 2009/10//
PB - EDP Sciences
VL - 43
IS - 4
SP - 375
EP - 386
AB - In this paper, we describe the methodology used to tackle France Telecom workforce scheduling problem (the subject of the Roadef Challenge 2007) and we report the results obtained on the different data sets provided for the competition. Since the problem at hand appears to be NP-hard and due to the high dimensions of the instance sets, we use a two-step heuristical approach. We first devise a problem-tailored heuristic that provides good feasible solutions and then we use a meta-heuristic scheme to improve the current results. The tailored heuristic makes use of sophisticated integer programming models and the corresponding sub-problems are solved using CPLEX while the meta-heuristic framework is a randomized local search algorithm. The approach herein described allowed us to rank 5th in this challenge.
LA - eng
KW - Workforce scheduling; schedule generation scheme; roadef challenge.; workforce scheduling; roadef challenge
UR - http://eudml.org/doc/250548
ER -

References

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  6. ILOG Inc., CPLEX Solver. (2006).  URIhttp://www.ilog.com
  7. R. Kolisch and S. Hartmann, Experimental evaluation of state-of-the-art heuristics for the resource-constrained project scheduling problem. Eur. J. Oper. Res.127 (2000) 394–407.  Zbl0985.90036
  8. R. Kolisch and S. Hartmann, Experimental investigations of heuristics for resource-constrained project scheduling: an update. Eur. J. Oper. Res.174 (2006) 23–37.  Zbl1116.90047
  9. H. Mahmoud, Pólya Urn Models. Taylor & Francis Group LLC – CRC Press (2008).  Zbl1149.60005
  10. D. Merkle, M. Middendorf and H. Schmeck, Ant colony optimization for resource-constrained project-scheduling, IEEE Trans. Evol. Comput.6 (2002) 333–346.  
  11.  URIhttp://www.g-scop.inpg.fr/ChallengeROADEF2007/
  12. E. Tsang and C. Voudouris, Fast local search and guided local search and their application to British Telecom's workforce scheduling problem. Technical Report CSM-246, Department of Computer Science, University of Essex, UK (1995).  Zbl0882.90102

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