Awadallah, M. A., Bolaji, A. L. a., & Al-Betar, M. A. (2015). A hybrid artificial bee colony for a nurse rostering problem. Applied Soft Computing, 35, 726-739.
Baeklund, J., & Klose, A. (2013). Exact and heuristic approaches to nurse scheduling. Aarhus University, Department of Mathematics,
Bagheri, M., Devin, A. G., & Izanloo, A. (2015). A two-stage stochastic programming for nurse scheduling in Razavi Hospital. Razavi International Journal of Medicine, 3(1).
Brest, J., Greiner, S., Boskovic, B., Mernik, M., & Zumer, V. (2006). Self-adapting control parameters in differential evolution: A comparative study on numerical benchmark problems. IEEE transactions on evolutionary computation, 10(6), 646-657.
Eskandari, A., & Ziarati, K. (2008). Nurse rostering using fuzzy logic: a case study.
Fatemi Ghomi, S., Arabzadeh, E., Karimi, B. (2018). A Multi Period Routing and Scheduling optimization Model for Home health Care Problem. Industrial Management Studies, 16(48), 1-30 [in Persian].
Foley, M. E. (2002). The nursing shortage and the quality of care. The New England journal of medicine, 347(14), 1118.
Fulcher, J. (2008). Computational intelligence: an introduction. In Computational intelligence: a compendium (pp. 3-78): Springer.
Glass, C. A., & Knight, R. A. (2010). The nurse rostering problem: A critical appraisal of the problem structure. European Journal of Operational Research, 202(2), 379-389.
Hall, R. W. (2012). Handbook of healthcare system scheduling: Springer.
Huang, H., Lin, W., Lin, Z., Hao, Z., & Lim, A. (2014). An evolutionary algorithm based on constraint set partitioning for nurse rostering problems. Neural Computing and Applications, 25(3-4), 703-715.
Huarng, F. (1997). Integer goal programming model for nursing scheduling: a case study. In Multiple Criteria Decision Making (pp. 634-643): Springer.
Ingels, J., & Maenhout, B. (2015). The impact of reserve duties on the robustness of a personnel shift roster: An empirical investigation. Computers & Operations Research, 61, 153-169.
Lagatie, R., Haspeslagh, S., & De Causmaecker, P. (2009). Negotiation Protocols for Distributed Nurse Rostering. Paper presented at the Proceedings of the 21st Benelux Conference on Artificial Intelligence.
Maass, K. L., Liu, B., Daskin, M. S., Duck, M., Wang, Z., Mwenesi, R., & Schapiro, H. (2017). Incorporating nurse absenteeism into staffing with demand uncertainty. Health care management science, 20(1), 141-155.
Parr, D., & Thompson, J. M. (2007). Solving the multi-objective nurse scheduling problem with a weighted cost function. Annals of Operations Research, 155(1), 279-288.
Pham, V. N., Le Thi, H. A., & Dinh, T. P. (2012). Solving nurse rostering problems by a multiobjective programming approach. Paper presented at the International Conference on Computational Collective Intelligence.
Price, K., Storn, R. M., & Lampinen, J. A. (2006). Differential evolution: a practical approach to global optimization: Springer Science & Business Media.
Rashidi Komijan, A., Gordani, A. (2019). An integrated mathematical model for aircraft routing and crew scheduling for airlines with multi fleet and multi maintenance hub. Industrial Management Studies, 17(55), 101-135 [in Persian].
Richardson, J. T., Palmer, M. R., Liepins, G. E., & Hilliard, M. R. (1989). Some guidelines for genetic algorithms with penalty functions. Paper presented at the Proceedings of the 3rd international conference on genetic algorithms.
Roy, S., Davim, J. P., & Kumar, K. (2017). Optimization of process parameters using Taguchi coupled genetic algorithm: machining in CNC lathe. In Mathematical Concepts and Applications in Mechanical Engineering and Mechatronics (pp. 67-93): IGI Global.
Santos, H. G., Toffolo, T. A., Gomes, R. A., & Ribas, S. (2016). Integer programming techniques for the nurse rostering problem. Annals of Operations Research, 239(1), 225-251.
Sharma, P., Sharma, N., & Sharma, H. (2016). Binomial crossover embedded shuffled frog leaping algorithm. Paper presented at the Computing, Communication and Automation (ICCCA), 2016 International Conference on.
Smet, P. (2016). Nurse rostering: models and algorithms for theory, practice and integration with other problems. 4OR, 14, 327–328.
Solos, I. P., Tassopoulos, I. X., & Beligiannis, G. N. (2013). A generic two-phase stochastic variable neighborhood approach for effectively solving the nurse rostering problem. Algorithms, 6(2), 278-308.
Storn, R., & Price, K. (2010). Differential evolution homepage. Available at: http://www. ICSI. Berkeley. edu/~ storn/code. html.