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Scheduling policies for multi-period services

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  • Núñez-del-Toro, Cristina
  • Fernández, Elena
  • Kalcsics, Jörg
  • Nickel, Stefan

Abstract

This paper discusses a multi-period service scheduling problem. In this problem, a set of customers is given who periodically require service over a finite time horizon. To satisfy the service demands, a set of operators is given, each with a fixed capacity in terms of the number of customers an operator can serve per period. The task is to determine for each customer the periods in which he will be visited by an operator such that the periodic service requests of the customers are adhered to and the total number of operators used over the time horizon is minimal. Two alternative policies for scheduling customer visits are considered. In the first one, a customer is visited just on time, i.e., in the period where he or she has a demand for service. The second policy allows service visits ahead of time. The rationale behind this policy is that allowing irregular visits may reduce the overall number of operators needed throughout the time horizon. To solve the problem, integer linear programming formulations are proposed for both policies and numerical experiments are presented that show the reduction in the number of operators used when visits ahead of time are allowed. As only small instances can be solved optimally, a heuristic algorithm is introduced in order to obtain good quality solutions and shorter computing times.

Suggested Citation

  • Núñez-del-Toro, Cristina & Fernández, Elena & Kalcsics, Jörg & Nickel, Stefan, 2016. "Scheduling policies for multi-period services," European Journal of Operational Research, Elsevier, vol. 251(3), pages 751-770.
  • Handle: RePEc:eee:ejores:v:251:y:2016:i:3:p:751-770
    DOI: 10.1016/j.ejor.2015.12.002
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    References listed on IDEAS

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    Cited by:

    1. Fernández, Elena & Kalcsics, Jörg & Núñez-del-Toro, Cristina, 2017. "A branch-and-price algorithm for the Aperiodic Multi-Period Service Scheduling Problem," European Journal of Operational Research, Elsevier, vol. 263(3), pages 805-814.
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