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An Implicit Goal Programming Model for the Tour Scheduling Problem Considering the Employee Work Preferences

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  • Seyda Topaloglu
  • Irem Ozkarahan

Abstract

Many organizations face employee scheduling problems under conditions of variable demand for service over the course of an operating day and across a planning horizon. These organizations are concerned with the tour scheduling problem that involves assigning shifts and break times to the work days of employees and allocating days off to individual work schedules. Nowadays, organizations try to adopt various scheduling flexibility alternatives to meet the fluctuating service demand. On the other hand, they have also realized that providing employee productivity and satisfaction is as much important as meeting the service demand. Up to date, tour scheduling solution approaches have neglected considering employee preferences and tried to develop work schedules for employees in a subsequent step. This paper presents a goal programming model that implicitly represents scheduling flexibility and also incorporates information about the preferred working patterns of employees. After solving the proposed model, a work schedule will be generated for each employee without requiring a further step for the assignment of shifts, break times, and work days to employees. The model is capable of handling multiple scheduling objectives, and it can produce optimal solutions in very short computing times. Copyright Kluwer Academic Publishers 2004

Suggested Citation

  • Seyda Topaloglu & Irem Ozkarahan, 2004. "An Implicit Goal Programming Model for the Tour Scheduling Problem Considering the Employee Work Preferences," Annals of Operations Research, Springer, vol. 128(1), pages 135-158, April.
    • Handle: RePEc:spr:annopr:v:128:y:2004:i:1:p:135-158:10.1023/b:anor.0000019102.68222.df
    DOI: 10.1023/B:ANOR.0000019102.68222.df
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    Citations

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    Cited by:

    1. Ferdinand Kiermaier & Markus Frey & Jonathan F. Bard, 2020. "The flexible break assignment problem for large tour scheduling problems with an application to airport ground handlers," Journal of Scheduling, Springer, vol. 23(2), pages 177-209, April.
    2. Salem Al-Yakoob & Hanif Sherali, 2007. "Mixed-integer programming models for an employee scheduling problem with multiple shifts and work locations," Annals of Operations Research, Springer, vol. 155(1), pages 119-142, November.
    3. Lin, Shih-Wei & Ying, Kuo-Ching, 2014. "Minimizing shifts for personnel task scheduling problems: A three-phase algorithm," European Journal of Operational Research, Elsevier, vol. 237(1), pages 323-334.
    4. Wolbeck, Lena Antonia, 2019. "Fairness aspects in personnel scheduling," Discussion Papers 2019/16, Free University Berlin, School of Business & Economics.
    5. S M Al-Yakoob & H D Sherali, 2008. "A column generation approach for an employee scheduling problem with multiple shifts and work locations," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(1), pages 34-43, January.
    6. Idris Addou & François Soumis, 2007. "Bechtold-Jacobs generalized model for shift scheduling with extraordinary overlap," Annals of Operations Research, Springer, vol. 155(1), pages 177-205, November.
    7. Yongjian Li & Jian Chen & Xiaoqiang Cai, 2007. "An integrated staff-sizing approach considering feasibility of scheduling decision," Annals of Operations Research, Springer, vol. 155(1), pages 361-390, November.
    8. Cinzia Colapinto & Raja Jayaraman & Simone Marsiglio, 2017. "Multi-criteria decision analysis with goal programming in engineering, management and social sciences: a state-of-the art review," Annals of Operations Research, Springer, vol. 251(1), pages 7-40, April.
    9. Mark W. Isken & Osman T. Aydas, 2022. "A tactical multi-week implicit tour scheduling model with applications in healthcare," Health Care Management Science, Springer, vol. 25(4), pages 551-573, December.
    10. Banu Sungur & Cemal Özgüven & Yasemin Kariper, 2017. "Shift scheduling with break windows, ideal break periods, and ideal waiting times," Flexible Services and Manufacturing Journal, Springer, vol. 29(2), pages 203-222, June.
    11. Marta Rocha & José Oliveira & Maria Carravilla, 2014. "A constructive heuristic for staff scheduling in the glass industry," Annals of Operations Research, Springer, vol. 217(1), pages 463-478, June.
    12. Jonas Ingels & Broos Maenhout, 2017. "Employee substitutability as a tool to improve the robustness in personnel scheduling," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(3), pages 623-658, July.
    13. Andreas Fügener & Jens O. Brunner, 2019. "Planning for Overtime: The Value of Shift Extensions in Physician Scheduling," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 732-744, October.
    14. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    15. Adibah Shuib & Faiq Izzuddin Kamarudin, 2019. "Solving shift scheduling problem with days-off preference for power station workers using binary integer goal programming model," Annals of Operations Research, Springer, vol. 272(1), pages 355-372, January.
    16. Şeyda Gür & Tamer Eren, 2018. "Scheduling and Planning in Service Systems with Goal Programming: Literature Review," Mathematics, MDPI, vol. 6(11), pages 1-16, November.

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