Solving a multiple-qualifications physician scheduling problem with multiple types of tasks by dynamic programming and variable neighborhood search

References

• Bard, J. F., Shu, Z., & Leykum, L. (2014). A network-based approach for monthly scheduling of residents in primary care clinics. Operations Research for Health Care, 3(4), 200–214. https://doi.org/10.1016/j.orhc.2014.08.002
   Google Scholar
• Bard, J. F., Shu, Z., Morrice, D. J., & Leykum, L. K. (2017). Constructing block schedules for internal medicine residents. IISE Transactions on Healthcare Systems Engineering, 7(1), 1–14. https://doi.org/10.1080/19488300.2016.1255284
   Google Scholar
• Bard, J. F., Shu, Z., Morrice, D. J., Leykum, L. K., & Poursani, R. (2016). Annual block scheduling for family medicine residency programs with continuity clinic considerations. IIE Transactions (Institute of Industrial Engineers), 48(9), 797–811.
   Web of Science ®Google Scholar
• Barger, L. K., Sullivan, J. P., Blackwell, T., O’Brien, C. S., St. Hilaire, M. A., Rahman, S. A., Phillips, A. J. K., Qadri, S., Wright, K. P., Segar, J. L., McGuire, J. K., Vitiello, M. V., de la Iglesia, H. O., Poynter, S. E., Yu, P. L., Zee, P., Sanderson, A. L., Halbower, A. C., Lockley, S. W., … Zee, P. C. (2019). Effects on resident work hours, sleep duration, and work experience in a randomized order safety trial evaluating resident-physician schedules (ROSTERS). Sleep, 42(8), zsz110. https://doi.org/10.1093/sleep/zsz110
   PubMed Web of Science ®Google Scholar
• Beliën, J., & Demeulemeester, E. (2008). A branch-and-price approach for integrating nurse and surgery scheduling. European Journal of Operational Research, 189(3), 652–668. https://doi.org/10.1016/j.ejor.2006.10.060
   Web of Science ®Google Scholar
• Bolaji, A. L., Bamigbola, A. F., & Shola, P. B. (2018). Late acceptance hill climbing algorithm for solving patient admission scheduling problem. Knowledge-Based Systems, 145, 197–206. https://doi.org/10.1016/j.knosys.2018.01.017
   Web of Science ®Google Scholar
• Bowers, M. R., Noon, C. E., Wu, W., & Bass, J. K. (2016). Neonatal physician scheduling at the University of Tennessee medical center. Interfaces, 46(2), 168–182. https://doi.org/10.1287/inte.2015.0839
   Web of Science ®Google Scholar
• Bruni, R., & Detti, P. (2014). A flexible discrete optimization approach to the physician scheduling problem. Operations Research for Health Care, 3(4), 191–199. https://doi.org/10.1016/j.orhc.2014.08.003
   Google Scholar
• Brunner, J. O., Bard, J. F., & Kolisch, R. (2010). Midterm scheduling of physicians with flexible shifts using branch and price. IIE Transactions, 43(2), 84–109. https://doi.org/10.1080/0740817X.2010.504685
   Web of Science ®Google Scholar
• Burke, E. K., & Curtois, T. (2014). New approaches to nurse rostering benchmark instances. European Journal of Operational Research, 237(1), 71–81. https://doi.org/10.1016/j.ejor.2014.01.039
   Web of Science ®Google Scholar
• Caporossi, G., Hansen, P., & Mladenović, N. (2016). Variable neighborhood search. In P. Siarry (Ed.), Metaheuristics (pp. 77–98). Springer International Publishing.
   Google Scholar
• Ceyhan, G., & Özpeynirci, Ö. (2016). A branch and price algorithm for the pharmacy duty scheduling problem. Computers & Operations Research, 72, 175–182. https://doi.org/10.1016/j.cor.2016.02.007
   Web of Science ®Google Scholar
• Chekuri, C., & Khanna, S. (2005). A polynomial time approximation scheme for the multiple knapsack problem. SIAM Journal on Computing, 35(3), 713–728. https://doi.org/10.1137/S0097539700382820
   Web of Science ®Google Scholar
• Damcı-Kurt, P., Zhang, M., Marentay, B., & Govind, N. (2019). Improving physician schedules by leveraging equalization: Cases from hospitals in U.S. Omega, 85, 182–193. https://doi.org/10.1016/j.omega.2018.06.011
   Web of Science ®Google Scholar
• Dellaert, N., & Jeunet, J. (2017). A variable neighborhood search algorithm for the surgery tactical planning problem. Computers & Operations Research, 84, 216–225. https://doi.org/10.1016/j.cor.2016.05.013
   Web of Science ®Google Scholar
• Erhard, M. (2021). Flexible staffing of physicians with column generation. Flexible Services and Manufacturing Journal, 33(1), 212–252. https://doi.org/10.1007/s10696-019-09353-8
   Web of Science ®Google Scholar
• Feng, Z. K., Niu, W. J., Cheng, C. T., & Liao, S. L. (2017). Hydropower system operation optimization by discrete differential dynamic programming based on orthogonal experiment design. Energy, 126, 720–732. https://doi.org/10.1016/j.energy.2017.03.069
   Web of Science ®Google Scholar
• Fréville, A. (2004). The multidimensional 0-1 knapsack problem: An overview. European Journal of Operational Research, 155(1), 1–21. https://doi.org/10.1016/S0377-2217(03)00274-1
   Web of Science ®Google Scholar
• Friedman, M. (1940). A comparison of alternative tests of significance for the problem of m rankings. The Annals of Mathematical Statistics, 11(1), 86–92. https://doi.org/10.1214/aoms/1177731944
   Google Scholar
• Fügener, A., Brunner, J. O., & Podtschaske, A. (2015). Duty and workstation rostering considering preferences and fairness: A case study at a department of anaesthesiology. International Journal of Production Research, 53(24), 7465–7487. https://doi.org/10.1080/00207543.2015.1082667
   Web of Science ®Google Scholar
• Güler, M. G., İdin, K., & Yilmaz Güler, E. (2013). A goal programming model for scheduling residents in an anesthesia and reanimation department. Expert Systems with Applications, 40(6), 2117–2126. https://doi.org/10.1016/j.eswa.2012.10.030
   Web of Science ®Google Scholar
• Gunawan, A., & Lau, H. C. (2013). Master physician scheduling problem. Journal of the Operational Research Society, 64(3), 410–425. https://doi.org/10.1057/jors.2012.48
   Web of Science ®Google Scholar
• Hansen, P., & Mladenović, N. (2001). Variable neighborhood search: Principles and applications. European Journal of Operational Research, 130(3), 449–467. https://doi.org/10.1016/S0377-2217(00)00100-4
   Web of Science ®Google Scholar
• Hansen, P., Mladenović, N., Moreno Pérez, J. A., & Moreno Pérez, J. A. (2010). Variable neighbourhood search: Methods and applications. Annals of Operations Research, 175(1), 367–407. https://doi.org/10.1007/s10479-009-0657-6
   Web of Science ®Google Scholar
• Islam, N. (2014). The dilemma of physician shortage and international recruitment in Canada. International Journal of Health Policy and Management, 3(1), 29–32. https://doi.org/10.15171/ijhpm.2014.53
   PubMedGoogle Scholar
• Kocatürk, F., & Özpeynirci, Ö. (2014). Variable neighborhood search for the pharmacy duty scheduling problem. Computers & Operations Research, 51, 218–226. https://doi.org/10.1016/j.cor.2014.06.001
   Web of Science ®Google Scholar
• Kong, M., Xu, J., Zhang, T., Lu, S., Fang, C., & Mladenovic, N. (2021). Energy-efficient rescheduling with time-of-use energy cost: Application of variable neighborhood search algorithm. Computers & Industrial Engineering, 156, 107286. https://doi.org/10.1016/j.cie.2021.107286
   Web of Science ®Google Scholar
• Krishnaiah, K., & Shahabudeen, P. (2012). Applied design of experiments and Taguchi methods. PHI Learning Private Limited.
   Google Scholar
• Lan, S., Fan, W., Yang, S., Pardalos, P. M., & Mladenovic, N. (2021). A survey on the applications of variable neighborhood search algorithm in healthcare management. Annals of Mathematics and Artificial Intelligence.
   PubMed Web of Science ®Google Scholar
• Lo, C. C., & Lin, T. H. (2011). A particle swarm optimization approach for physician scheduling in a hospital emergency department. Proceedings – 2011 7th International Conference on Natural Computation, ICNC 2011 (Vol. 4, pp. 1929–1933). IEEE.
   Google Scholar
• Mafakheri, F., Breton, M., & Ghoniem, A. (2011). Supplier selection-order allocation: A two-stage multiple criteria dynamic programming approach. International Journal of Production Economics, 132(1), 52–57. https://doi.org/10.1016/j.ijpe.2011.03.005
   Web of Science ®Google Scholar
• Mankowska, D. S., Meisel, F., & Bierwirth, C. (2014). The home health care routing and scheduling problem with interdependent services. Health Care Management Science, 17(1), 15–30. https://doi.org/10.1007/s10729-013-9243-1
   PubMed Web of Science ®Google Scholar
• Mattos Ribeiro, G., Regis Mauri, G., & Antonio Nogueira Lorena, L. (2011). A simple and robust Simulated Annealing algorithm for scheduling workover rigs on onshore oil fields. Computers & Industrial Engineering, 60(4), 519–526. https://doi.org/10.1016/j.cie.2010.12.006
   Web of Science ®Google Scholar
• McAbee, J. H., Ragel, B. T., McCartney, S., Jones, G. M., Michael, L. M., DeCuypere, M., Cheng, J. S., Boop, F. A., & Klimo, P. (2015). Factors associated with career satisfaction and burnout among US neurosurgeons: Results of a nationwide survey. Journal of Neurosurgery, 123(1), 161–173. https://doi.org/10.3171/2014.12.JNS141348
   PubMed Web of Science ®Google Scholar
• Mladenović, N., Alkandari, A., Pei, J., Todosijević, R., & Pardalos, P. M. (2020). Less is more approach: Basic variable neighborhood search for the obnoxious p-median problem. International Transactions in Operational Research, 27(1), 480–493. https://doi.org/10.1111/itor.12646
   Web of Science ®Google Scholar
• Mladenović, N., & Hansen, P. (1997). Variable neighborhood search. Computers & Operations Research, 24(11), 1097–1100. https://doi.org/10.1016/S0305-0548(97)00031-2
   Web of Science ®Google Scholar
• Mladenović, N., Kratica, J., Kovačević-Vujčić, V., & Čangalović, M. (2012). Variable neighborhood search for metric dimension and minimal doubly resolving set problems. European Journal of Operational Research, 220(2), 328–337. https://doi.org/10.1016/j.ejor.2012.02.019
   Web of Science ®Google Scholar
• Nickabadi, A., Ebadzadeh, M. M., & Safabakhsh, R. (2011). A novel particle swarm optimization algorithm with adaptive inertia weight. Applied Soft Computing, 11(4), 3658–3670. https://doi.org/10.1016/j.asoc.2011.01.037
   Web of Science ®Google Scholar
• Pei, J., Liu, X., Pardalos, P. M., Fan, W., Yang, S., & Wang, L. (2014). Application of an effective modified gravitational search algorithm for the coordinated scheduling problem in a two-stage supply chain. The International Journal of Advanced Manufacturing Technology, 70(1–4), 335–348. https://doi.org/10.1007/s00170-013-5263-8
   Web of Science ®Google Scholar
• Pei, J., Song, Q., Liao, B., Liu, X., & Pardalos, P. M. (2021). Parallel-machine serial-batching scheduling with release times under the effects of position-dependent learning and time-dependent deterioration. Annals of Operations Research, 298(1-2), 407–444. https://doi.org/10.1007/s10479-020-03555-2
   Web of Science ®Google Scholar
• Puente, J., Gómez, A., Fernández, I., & Priore, P. (2009). Medical doctor rostering problem in a hospital emergency department by means of genetic algorithms. Computers & Industrial Engineering, 56(4), 1232–1242. https://doi.org/10.1016/j.cie.2008.07.016
   Web of Science ®Google Scholar
• Rahimian, E., Akartunalı, K., & Levine, J. (2017). A hybrid integer programming and variable neighbourhood search algorithm to solve nurse rostering problems. European Journal of Operational Research, 258(2), 411–423. https://doi.org/10.1016/j.ejor.2016.09.030
   Web of Science ®Google Scholar
• Souki, M. (2011). Operating theatre scheduling with fuzzy durations. Journal of Applied Operational Research, 3(3), 177–191.
   Google Scholar
• Stolletz, R., & Brunner, J. O. (2012). Fair optimization of fortnightly physician schedules with flexible shifts. European Journal of Operational Research, 219(3), 622–629. https://doi.org/10.1016/j.ejor.2011.10.038
   Web of Science ®Google Scholar
• Tohidi, M., Kazemi Zanjani, M., & Contreras, I. (2019). Integrated physician and clinic scheduling in ambulatory polyclinics. Journal of the Operational Research Society, 70(2), 177–191. https://doi.org/10.1080/01605682.2017.1421853
   Web of Science ®Google Scholar
• Volland, J., Fügener, A., & Brunner, J. O. (2017). A column generation approach for the integrated shift and task scheduling problem of logistics assistants in hospitals. European Journal of Operational Research, 260(1), 316–334. https://doi.org/10.1016/j.ejor.2016.12.026
   Web of Science ®Google Scholar
• Wang, C.-W., Sun, L.-M., Jin, M.-H., Fu, C.-J., Liu, L., Chan, C.-H., & Kao, C.-Y. (2007). A genetic algorithm for resident physician scheduling problem. In Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation - GECCO ’07 (p. 2203). ACM.
   Google Scholar
• Zheng, Z., Liu, X., & Gong, X. (2017). A simple randomized variable neighbourhood search for nurse rostering. Computers & Industrial Engineering, 110, 165–174. https://doi.org/10.1016/j.cie.2017.05.027
   Web of Science ®Google Scholar