Skip to main content
SpringerLink
Log in

The Effects of Shift Generation on Staff Rostering

  • Conference paper
  • First Online:
Dynamics of Information Systems (DIS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14321))

Included in the following conference series:

Abstract

To the best of our knowledge, this is the first paper to examine the effect of shift structures on staff rostering optimization. The study showed that the generated shift structures have a significant effect on optimizing the staff rosters. The study also showed that we should allow longer working days, because they imply better consideration of the stress and risk factors introduced by the Finnish Institute of Occupational Health. The PEASTP metaheuristic, a computational intelligence framework, was used to justify the findings. The results were obtained using a real-world instance from a Finnish contact center.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 49.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 64.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Musliu, N., Schaerf, A., Slany, W.: Local search for shift design. Eur. J. Oper. Res. 153(1), 51–64 (2004)

    Article  MathSciNet  Google Scholar 

  2. Di Gaspero, L., Gärtner, J., Kortsarz, G., Musliu, N., Schaerf, A., Slany, W.: The minimum shift design problem. Ann. Oper. Res. 155, 79–105 (2007)

    Article  MathSciNet  Google Scholar 

  3. Kyngäs, N., Goossens, D., Nurmi, K., Kyngäs, J.: Optimizing the unlimited shift generation problem. In: Di Chio, C., et al. (eds.) Applications of Evolutionary Computation. Lecture Notes in Computer Science, vol. 7248, pp.508–518. Springer, Berlin, Heidelberg (2012). https://doi.org/10.1007/978-3-642-29178-4_51

  4. Kyngäs, N., Nurmi, K., Kyngäs, J.: Solving the person-based multitask shift generation problem with breaks. In: Proceedings of the 5th International Conference on Modeling, Simulation and Applied Optimization, pp. 1–8 (2013)

    Google Scholar 

  5. Dowling, D., Krishnamoorthy, M., Mackenzie, H., Sier, H.: Staff rostering at a large international airport. Ann. Oper. Res. 72, 125–147 (1997)

    Article  Google Scholar 

  6. Valls, V., Perez, A., Quintanilla, S.: A graph colouring model for assigning a heterogenous workforce to a given schedule. Eur. J. Oper. Res. 90, 285–302 (1996)

    Article  Google Scholar 

  7. Krishnamoorthy, M., Ernst, A.T.: The personnel task scheduling problem. Optim. Methods Appl., 343–367 (2001)

    Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  9. Jansen, K.: An approximation algorithm for the license and shift class design problem. Eur. J. Oper. Res. 73, 127–131 (1994)

    Article  Google Scholar 

  10. Kroon, L.G., Salomon, M., Van Wassenhove, L.N.: Exact and approximation algorithms for the tactical fixed interval scheduling problem. Oper. Res. 45(4), 624–638 (1997)

    Article  MathSciNet  Google Scholar 

  11. Kolen, A.W.J., Lenstra, J.K., Papadimitriou, C.H., Spieksma, F.C.R.: Interval scheduling: a survey. Nav. Res. Logist. 54(5), 530–543 (2007)

    Article  MathSciNet  Google Scholar 

  12. Nurmi, K., Kyngäs, N., Kyngäs, J.: Workforce optimization: the general task-based shift generation problem. IAENG Int. J. Appl. Math. 49(4), 393–400 (2019)

    Google Scholar 

  13. Kyngäs, N., Nurmi, K.: The extended shift minimization personnel task scheduling problem. In: Position and Communication Papers of the 16th Conference on Computer Science and Intelligence Systems, vol. 26, pp. 65–74 (2021)

    Google Scholar 

  14. Garey, M.R., Johnson, D.S.: Computers and intractability: a guide to the theory of NP-completeness. Freeman (1979)

    Google Scholar 

  15. Tien, J., Kamiyama, A.: On manpower scheduling algorithms. SIAM Rev. 24(3), 275–287 (1982)

    Article  MathSciNet  Google Scholar 

  16. Lau, H.C.: On the complexity of manpower shift scheduling. Comput. Oper. Res. 23(1), 93–102 (1996)

    Article  Google Scholar 

  17. Marx, D.: Graph coloring problems and their applications in scheduling. Periodica Polytechnica Ser. El. Eng. 48, 5–10 (2004)

    Google Scholar 

  18. Bruecker, P., Qu, R., Burke, E.: Personnel scheduling: models and complexity. Eur. J. Oper. Res. 210(3), 467–473 (2011)

    Article  MathSciNet  Google Scholar 

  19. Jackson,W.K., Havens, W.S., Dollard, H.: Staff scheduling: a simple approach that worked. Technical Report CMPT97-23, School of Computing Science, Simon Fraser University, Canada (1997)

    Google Scholar 

  20. Lapegue, T., Bellenguez-Morineau, O., Prot, D.: A constraint-based approach for the shift design personnel task scheduling problem with equity. Comput. Oper. Res. 40(10), 2450–2465 (2013)

    Article  Google Scholar 

  21. Prot, D., Lapgue, T., Bellenguez-Morineau, O.: A two-base method for the shift design and personnel task scheduling problem with equity objective. Int. J. Prod. Res. 53(24), 7286–7298 (2015)

    Article  Google Scholar 

  22. Smet, P., Ernst, A.T., Vanden Berghe, G.: Heuristic decomposition approaches for an integrated task scheduling and personnel rostering problem. Comput. Oper. Res. 76, 60–72 (2016)

    Article  MathSciNet  Google Scholar 

  23. The Finnish Institute of Occupational Health, “Recommendations for shift work”. https://www.ttl.fi/teemat/tyohyvinvointi-ja-tyokyky/tyoaika/vuorotyo/tyoaikojen-kuormittavuuden-arviointi. Accessed 17 Mar 2023. (in Finnish)

  24. Karhula, K., et al.: Are changes in objective working hour characteristics associated with changes in work-life conflict among hospital employees working shifts? A 7-year follow-up. Occup. Environ. Med. 75(6), 407–411 (2018)

    Article  Google Scholar 

  25. Karhula, K., Hakola, T., Koskinen, A., Ojajärvi, A., Kivimäki, M., Härmä, M.: Permanent night workers’ sleep and psychosocial factors in hospital work. a comparison to day and shift work. Chronobiol. Int. 35(6), 785–794 (2018)

    Article  Google Scholar 

  26. Nurmi, K., Kyngäs, J., Kyngäs, N.: Staff rostering optimization: ideal recommendations vs. real-world computing challenges. In: Arai, K. (ed.) Intelligent Computing. Lecture Notes in Networks and Systems, vol. 283, pp. 274–291. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-80119-9_15

    Chapter  Google Scholar 

  27. Nurmi, K., Kyngäs, J., Kyngäs, N.: Synthesis of employer and employee satisfaction - case nurse rostering in a finnish hospital. J. Adv. Inf. Technol. 7(2), 97–104 (2016)

    Google Scholar 

  28. Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Optimization by simulated annealing. Science 220, 671–680 (1983)

    Article  MathSciNet  Google Scholar 

  29. Glover, F.: Future paths for integer programming and links to artificial intelligence. Comput. Oper. Res. 13(5), 533–549 (1986)

    Article  MathSciNet  Google Scholar 

  30. Goldberg, D.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley, USA (1989)

    Google Scholar 

  31. Mladenovic, N., Hansen, P.: Variable neighborhood search. Comput. Oper. Res. 24(11), 1097–1100 (1997)

    Article  MathSciNet  Google Scholar 

  32. Dees, W.A., Smith II, R.: Performance of interconnection rip-up and reroute strategies. In: 18th Design Automation Conference, pp. 382–390 (1981)

    Google Scholar 

  33. Schrimpf, G., Schneider, K., Stamm-Wilbrandt, H., Dueck, W.: Record breaking optimization results using the ruin and recreate principle. J. Comput. Phys. 159, 139–171 (2000)

    Article  MathSciNet  Google Scholar 

  34. Glover, F.: New ejection chain and alternating path methods for traveling salesman problems. In: Computer Science and Operations Research: New Developments in Their Interfaces, pp. 449–509 (1992)

    Google Scholar 

  35. Kyngäs, N., Nurmi, K., Kyngäs, J.: Crucial Components of the PEAST algorithm in solving real-world scheduling problems. LNSE, 230–236 (2013). https://doi.org/10.7763/LNSE.2013.V1.51

  36. Kyngäs, N., Nurmi, K., Kyngäs, J.: Workforce scheduling using the PEAST algorithm. In: Ao, S.-I. (ed.) IAENG Transactions on Engineering Technologies. Lecture Notes in Electrical Engineering, vol. 275, pp. 359–372. Springer, USA (2014). https://doi.org/10.1007/978-94-007-7684-5_25

    Chapter  Google Scholar 

  37. Nurmi, K., Kyngäs, J., Järvelä, A.I.: Ten-year evolution and the experiments in scheduling a major ice hockey league. In: Daniel Hak (ed.) An in Depth Guide to Sports, Nova Science Publishers, pp 169–207 (2018)

    Google Scholar 

  38. Kyngäs, N., Nurmi, K., Goossens, D.: The general task-based shift generation problem: formulation and benchmarks. In: Proceedings of the 9th Multidisciplinary International Scheduling Conference: Theory and Applications (MISTA), Ningbo, China (2019)

    Google Scholar 

  39. Nurmi, K., Kyngäs, J., Kyngäs, N.: Practical recommendations for staff rostering justified by real-world optimization. In: Proceedings of the 11th International Conference on Health and Social Care Information Systems and Technologies (HCist) (2022)

    Google Scholar 

  40. Vedaa, Ø., et al.: Long working hours are inversely related to sick leave in the following 3 months: a 4-year registry study. Int. Arch. Occup. Environ. Health 92, 457–466 (2019)

    Article  Google Scholar 

  41. Karhula, K., et al.: 12 tunnin vuorojärjestelmien turvallinen ja työhyvinvointia edistävä toteuttaminen teollisuudessa. Report 114114, Finnish Institute of Occupational Health (2016). (in Finnish)

    Google Scholar 

  42. Roenneberg, T., et al.: Epidemiology of the human circadian clock. Sleep Med. Rev. 11(6), 429–438 (2007)

    Article  Google Scholar 

  43. Roenneberg, T., et al.: A marker for the end of adolescence. Current Biol. 14(24), R1038–R1039 (2004)

    Article  Google Scholar 

  44. Nijp, H.H., Beckers, D.G., Geurts, S.A.: Systematic review on the association between employee worktime control and work-non-work balance, health and well-being, and job-related outcomes. Scand. J. Work Environ. Health 38, 299–313 (2012)

    Article  Google Scholar 

  45. Wittmer, J., Shepard, A.K., James, E., Martin, J.E.: Schedule preferences, congruence and employee outcomes in unionized shift workers. Am. J. Bus. 30(1), 92–110 (2015)

    Article  Google Scholar 

  46. Sumathi, N., Parimala, S.: Impact of HR benefits on employee’s retention in surface transportation firms operating in Tamil Nadu. Int. J. Asian Dev. Stud. 28(6), 483–487 (2015)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Satakunta University of Applied Sciences, Satakunnankatu 23, 28130, Pori, Finland

    Kimmo Nurmi & Jari Kyngäs

  2. University of Turku, 20014, Turun yliopisto, Finland

    Nico Kyngäs

Authors
  1. Kimmo Nurmi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jari Kyngäs
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nico Kyngäs
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kimmo Nurmi .

Editor information

Editors and Affiliations

  1. Jan Evangelista Purkyně University, Ústí nad Labem-město, Czech Republic

    Hossein Moosaei

  2. Charles University, Prague, Czech Republic

    Milan Hladík

  3. University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Nurmi, K., Kyngäs, J., Kyngäs, N. (2024). The Effects of Shift Generation on Staff Rostering. In: Moosaei, H., Hladík, M., Pardalos, P.M. (eds) Dynamics of Information Systems. DIS 2023. Lecture Notes in Computer Science, vol 14321. Springer, Cham. https://doi.org/10.1007/978-3-031-50320-7_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-50320-7_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-50319-1

  • Online ISBN: 978-3-031-50320-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation