Öncelik Seviyelerine Sahip Çoklu Yetenek Gerektiren İşler için Ekip Oluşturma, Çizelgeleme ve Rotalama

Öz

Bu çalışmada, tüm saha hizmet operasyonlarında gözlemlenen, çoklu yetenek gereksinimi içeren işgücü rotalama ve çizelgeleme problemi ele alınmıştır. Problem, gerçek hayatta enerji dağıtım şirketlerinin günlük olarak karşılaştığı bir planlama probleminden yola çıkılarak tanımlanmıştır. Amaç, farklı konumları, öncelikleri ve yetenek gereksinimleri olan işler için; uygun teknisyen ekiplerinin ve sıralı iş listelerinin optimal bir şekilde belirlenmesidir. Öncelikle, problem için iki öncelikli amaç fonksiyonu bulunan bir matematiksel model geliştirilmiştir. Problem boyutu büyüdükçe modelin kabul edilebilir sürede ve kalitede çözüm vermemesi nedeniyle,  büyük ölçekli problemler için kısa sürede kaliteli çözümler üreten, üç aşamalı bir sezgisel yöntem geliştirilmiştir. Geliştirilen yöntemin etkinliği hem rastgele türetilmiş, hem de gerçekçi veri kümeleri üzerinde gösterilmiştir.

Anahtar Kelimeler

• İşgücü çizelgeleme ve rotalama,Modelleme,Sezgisel yöntemler,Takım oluşturma,Çok amaçlı karar verme

Forming, Scheduling and Routing Field Service Teams for Multi-Skill Prioritized Tasks

Öz

In this research, we study the multi-skill workforce scheduling and routing problem that arises in all field service operations. The problem originates from a daily planning problem faced by the electricity distribution companies. Given a set of geographically dispersed tasks with different priorities and skill requirements, and a set of technicians with different skills; the objective is to form teams of technicians while assigning a sequence of tasks to each team in an optimal manner.  First, we develop a mathematical model that has two prioritized objective functions for the problem. Since the solution time and quality of the model degrades quickly as the problem size increases, we devise a three-phased heuristic that generates good solutions efficiently for large-scale problems. We demonstrate the performance of the heuristic through randomly generated and realistic problem instances.

Anahtar Kelimeler

• Workforce scheduling and routing,Modelling,Heuristics,Team forming,Multi objective decision making

Kaynakça

1. [1] Fikar, C. and Hirsch P., 2016. Home health care routing and scheduling: A review, Computers & Operations Research, 77, 86-95, 2017.
2. [2] Cheng, E. and Rich, J. L., 1998. A home health care routing and scheduling problem, Technical Report 98-04, Computational and Applied Mathematics, Rice University
3. [3] Eveborn, P, Rönnqvist, M, Einarsdottir, H, Eklund, M, Lidén, K, Almroth, M., 2009. Operations Research Improves Quality and Efficiency in Home Care, Interfaces, Vol. 39, No. 1, 18-34, DOI 10.1287/inte.1080.0411
4. [4] Cordeau, J.-F., Laporte, G., Pasin, F., and Ropke, S., 2010. Scheduling Technicians and Tasks in a Telecommunications Company, Journal of Scheduling, 13, 393–409. 18
5. [5] Misir, M., Smet, P., Verbeeck, K., and Vanden Berghe, G. 2011. Security personnel routing and rostering: a hyper-heuristic approach. In Proceedings of the 3rd International Conference on Applied Operational Research, ICAOR2011, Istanbul, Turkey, pages 193–205
6. [6] Allaoua, H., Borne, S., L´etocart, L., and Calvo, R. W., 2013. A matheuristic approach for solving a home health care problem, Electronic Notes in Discrete Mathematics, 41 (0):471 – 478, 2013
7. [7] Kovacs, A., Parragh, A. A., Doerner, K. F., Hartl, R. F., 2012. Adaptive large neighborhood search for service technician routing and scheduling problems, Journal of Scheduling, 15(5) 579-600.
8. [8] Trautsamwieser, A., & Hirsch, P., 2014. A branch-price-and-cut approach for solving the medium-term home health care planning problem, Networks 64(3), 143-159

9. [9] Zamorano, E., & Stolletz, R., 2016. Branch-and-price approaches for the Multiperiod Technician Routing and Scheduling Problem, European Journal of Operational Research, 257(1), 55–68
10. [10] Fırat, M. and Hurkens, C. A. J., 2012. An improved MIP-based approach for a multi-skill workforce scheduling problem, Journal of Scheduling, vol. 15, pp. 363-380
11. [11] Rasmussen, M. S., Justesen, T., Dohn, A., & Larsen, J. (2012). The home care crew scheduling problem: Preference-based visit clustering and temporal dependencies. European Journal of Operational Research, 219(3), 598–610
12. [12] Hiermann, G., Puchinger, J., Ropke, S., and Hartl, R. F., 2015. The Electric Fleet Size and Mix Vehicle Routing Problem with Time Windows and Recharging Stations, Transportation Science. In press.
13. [13] Misir, M., Smet, P., & Vanden Berghe, G., 2015. An analysis of generalised heuristics for vehicle routing and personnel rostering problems. Journal of the Operational Research Society, 66(5), 858–870.
14. [14] Fosgerau, M., Engelson, L., 2011. The value of travel time variance. Transportation Research Part B 45, 1–8.
15. [15] Bostel, N., Dejax, P., Guez, P., & Tricoire, F., 2008. Multiperiod planning and routing on a rolling horizon for field force optimization logistics. In Bruce Golden, S. Raghavan, & Edward Wasil (Eds.). The vehicle routing problem: Latest advances and new challenges (43, pp. 503–525).
16. [16] Barrera, D., Velasco, N., & Amaya, C.-A., 2012. A network-based approach to the multi-activity combined timetabling and crew scheduling problem: Workforce scheduling for public health policy implementation. Computers & Industrial Engineering, 63(4), 802–812.
17. [17] Goel, A., Meisel, F., 2013. Workforce routing and scheduling for electricity network maintenance with downtime minimization. European Journal of Operational Research 231 (1), 210–228
18. [18] Francis, P.M., Smilowitz, K.R., Tzur, M., 2008. The period vehicle routing problem and its extensions. In: Golden BL, Raghavan S, Wasil E, editors. The vehicle routing problem: latest advances and new challenges.
19. [19] Blakeley, F., Bozkaya, B., Cao, B., Hall, W., Knolmajer, J., 2003. Optimizing periodic maintenance operations for Schindler Elevator Corporation. Interfaces 33 (1), 67–79
20. [20] Tang, H., Millerhooks, E. and Tomastik, R., 2007. Scheduling technicians for planned maintenance of geographically distributed equipment. Transportation Research Part E – Logistics and Transportation Review 43 (2007) 591–609
21. [21] Shao, Y., Jonathan, F. B. and Jarrah, A. I., 2012. The therapist routing and scheduling problem, IIE Trans. Oper. Eng. Anal. 44 (10) (2012) 868–893
22. [22] Bard, J. F., Shao, Y. and Jarrah, A. I., 2014. A sequential GRASP for the therapist routing and scheduling problem, J. Sched. 17 (2) (2014) 109–133.
23. [23] Hindle, T., Hindle, A., Spollent, M., 2000. Resource allocation modelling for homebased health and social care services in areas having differential population density levels: a case study in Northern Ireland. Health Services Management Research 13, 164–169
24. [24] Rest K. D., Hirsch P., 2015. Daily scheduling of home health care services using time-dependent public transport, Flexible Services and Manufacturing Journal.
25. [25] Lanzarone, E., Matta, A., 2014. Robust nurse-to-patient assignment in home care services to minimize overtimes under continuity of care, Oper. Res. Health Care 3 (2), 48–58.
26. [26] Yuan, B., Liu, R., & Jiang, Z., 2015. A branch-and-price algorithm for the home health care scheduling and routing problem with stochastic service times and skill requirements, International Journal of Production Research, 53(24), 7450–7464
27. [27] Dutot, P., Laugier, A. & Bustos, A., 2006. Technicians and Interventions Scheduling for Telecommunications. Technical report, France Telecom R&D. 18