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International Conference on Intelligent Decision Technologies

IDT 2017: Intelligent Decision Technologies 2017 pp 71–81Cite as

Applying the Intelligent Decision Heuristic to Solve Large Scale Technician and Task Scheduling Problems

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 72))

Abstract

Scheduling personnel to complete tasks is a complex combinatorial optimisation problem. In large organisations, finding quality solutions is of paramount importance due to the costs associated with staffing. In this paper we have generated and solved a set of novel large scale technician and task scheduling problems. The datasets include complexities such as priority levels, precedence constraints, skill requirements, teaming and outsourcing. The problems are considerably larger than those featured previously in the literature and are more representative of industrial scale problems, with up to 2500 jobs. We present our data generator and apply two heuristics, the intelligent decision heuristic and greedy heuristic, to provide a comparative analysis.

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References

  1. Burke, E., De Causmaecker, P., Berghe, G.V.: A hybrid tabu search algorithm for the nurse rostering problem. In: Asia-Pacific Conference on Simulated Evolution and Learning, pp. 187–194. Springer (1998)

    Google Scholar 

  2. Cordeau, J.F., Laporte, G., Pasin, F., Ropke, S.: Scheduling technicians and tasks in a telecommunications company. J. Sched. 13(4), 393–409 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  3. Crispin, A., Syrichas, A.: Quantum annealing algorithm for vehicle scheduling. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics, pp. 3523–3528. IEEE (2013)

    Google Scholar 

  4. Dutot, P.F., Laugier, A., Bustos, A.M.: Technicians and Interventions Scheduling for Telecommunications. France Telecom R&D, Lannion (2006)

    Google Scholar 

  5. Ernst, A.T., Jiang, H., Krishnamoorthy, M., Sier, D.: Staff scheduling and rostering: a review of applications, methods and models. Eur. J. Oper. Res. 153(1), 3–27 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  6. Estellon, B., Gardi, F., Nouioua, K.: High-performance local search for task scheduling with human resource allocation. In: Engineering Stochastic Local Search Algorithms, Designing, Implementing and Analyzing Effective Heuristics, pp. 1–15. Springer (2009)

    Google Scholar 

  7. Hashimoto, H., Boussier, S., Vasquez, M., Wilbaut, C.: A grasp-based approach for technicians and interventions scheduling for telecommunications. Ann. Oper. Res. 183(1), 143–161 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  8. Haugen, D.L., Hill, A.V.: Scheduling to improve field service quality*. Decis. Sci. 30(3), 783–804 (1999)

    Article  Google Scholar 

  9. Hurkens, C.A.: Incorporating the strength of MIP modeling in schedule construction. RAIRO-Oper. Res. 43(04), 409–420 (2009)

    Article  MATH  Google Scholar 

  10. Khalfay, A., Crispin, A., Crockett, K.: Solving technician and task scheduling problems with an intelligent decision heuristic. In: Intelligent Decision Technologies 2016, pp. 63–75. Springer (2016)

    Google Scholar 

  11. Kovacs, A.A., Parragh, S.N., Doerner, K.F., Hartl, R.F.: Adaptive large neighborhood search for service technician routing and scheduling problems. J. Sched. 15(5), 579–600 (2012)

    Article  MathSciNet  Google Scholar 

  12. Krishnamoorthy, M., Ernst, A.T., Baatar, D.: Algorithms for large scale shift minimisation personnel task scheduling problems. Eur. J. Oper. Research 219(1), 34–48 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  13. Pillac, V., Guéret, C., Medaglia, A.: On the dynamic technician routing and scheduling problem. In: Proceedings of the 5th International Workshop on Freight Transportation and Logistics (ODYSSEUS) (2012)

    Google Scholar 

  14. Pillac, V., Gueret, C., Medaglia, A.L.: A parallel matheuristic for the technician routing and scheduling problem. Optim. Lett. 7(7), 1525–1535 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  15. Society, F.O.R.: What is the roadef 2007 challenge (2016). http://challenge.roadef.org/2007/en/

  16. Solomon, M.M.: Algorithms for the vehicle routing and scheduling problems with time window constraints. Oper. Res. 35(2), 254–265 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  17. Titiloye, O., Crispin, A.: Quantum annealing of the graph coloring problem. Discrete Optim. 8(2), 376–384 (2011)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

This research is sponsored by ServicePower Technologies PLC, a worldwide leader in providing innovative mobile workforce management solutions, in cooperation with Manchester Metropolitan University and KTP.

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Authors and Affiliations

  1. Department of Computing, Mathematics and Digital Technology, Manchester Metropolitan University, Manchester, UK

    Amy Khalfay, Alan Crispin & Keeley Crockett

Authors
  1. Amy Khalfay
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  2. Alan Crispin
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  3. Keeley Crockett
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Corresponding author

Correspondence to Amy Khalfay .

Editor information

Editors and Affiliations

  1. Maritime University , Gdynia, Poland

    Ireneusz Czarnowski

  2. Bournemouth University and KES International, Poole, Dorset, United Kingdom

    Robert J. Howlett

  3. University of Canberra, Canberra, Aust Capital Terr, Australia

    Lakhmi C. Jain

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Khalfay, A., Crispin, A., Crockett, K. (2018). Applying the Intelligent Decision Heuristic to Solve Large Scale Technician and Task Scheduling Problems. In: Czarnowski, I., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies 2017. IDT 2017. Smart Innovation, Systems and Technologies, vol 72. Springer, Cham. https://doi.org/10.1007/978-3-319-59421-7_7

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  • DOI: https://doi.org/10.1007/978-3-319-59421-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59420-0

  • Online ISBN: 978-3-319-59421-7

  • eBook Packages: EngineeringEngineering (R0)

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