References
- Agarwal, A., Colak, S., & Erenguc, S. (2011). A neurogenetic approach for the resource-constrained project scheduling problem. Computers & Operations Research, 38(1), 44–50. doi:10.1016/j.cor.2010.01.007
- Al-Turki, U., Duffuaa, S., & Bendaya, M. (2019). Trends in turnaround maintenance planning: Literature review. Journal of Quality in Maintenance Engineering, 25(2), 253–271. doi:10.1108/JQME-10-2017-0074
- Blazewicz, J., Lenstra, J. K., & Kan, A. R. (1983). Scheduling subject to resource constraints: Classification and complexity. Discrete Applied Mathematics, 5(1), 11–24. doi:10.1016/0166-218X(83)90012-4
- Boctor, F. F. (1990). Some efficient multi-heuristic procedures for resource-constrained project scheduling. European Journal of Operational Research, 49(1), 3–13. doi:10.1016/0377-2217(90)90116-S
- Coelho, J., & Vanhoucke, M. (2018). An exact composite lower bound strategy for the resource-constrained project scheduling problem. Computers & Operations Research, 93, 135–150. doi:10.1016/j.cor.2018.01.017
- Demeulemeester, E., & Herroelen, W. (1992). A branch-and-bound procedure for the multiple resource-constrained project scheduling problem. Management Science, 38(12), 1803–1818. doi:10.1287/mnsc.38.12.1803
- Dorndorf, U., Pesch, E., & Phan-Huy, T. (2000). A branch-and-bound algorithm for the resource-constrained project scheduling problem. Mathematical Methods of Operations Research (Zor), 52(3), 413–439. doi:10.1007/s001860000091
- Ebrahimipour, V., Najjarbashi, A., & Sheikhalishahi, M. (2015). Multi-objective modeling for preventive maintenance scheduling in a multiple production line. Journal of Intelligent Manufacturing, 26(1), 111–122. doi:10.1007/s10845-013-0766-6
- Fuqiong, Z., Zhigang, T., & Yong, Z. (2013). Uncertainty quantification in gear remaining useful life prediction through an integrated prognostics method. IEEE Transactions on Reliability, 62(1), 146–159. doi:10.1109/TR.2013.2241216
- Hartmann, S., & Briskorn, D. (2010). A survey of variants and extensions of the resource-constrained project scheduling problem. European Journal of Operational Research, 207(1), 1–14. doi:10.1016/j.ejor.2009.11.005
- Jarboui, B., Damak, N., Siarry, P., & Rebai, A. (2008). A combinatorial particle swarm optimization for solving multi-mode resource-constrained project scheduling problems. Applied Mathematics and Computation, 195(1), 299–308. doi:10.1016/j.amc.2007.04.096
- Khorasgani, H., Biswas, G., & Sankararaman, S. (2016). Methodologies for system-level remaining useful life prediction. Reliability Engineering & System Safety, 154, 8–18. doi:10.1016/j.ress.2016.05.006
- Kolisch, R. (1996). Efficient priority rules for the resource-constrained project scheduling problem. Journal of Operations Management, 14(3), 179–192. doi:10.1016/0272-6963(95)00032-1
- Kolisch, R., & Hartmann, S. (1999). Heuristic algorithms for the resource-constrained project scheduling problem: Classification and computational analysis. In Jan Węglarz (ed.), Project scheduling (pp. 147–178). Springer.
- Kolisch, R., & Hartmann, S. (2006). Experimental investigation of heuristics for resource-constrained project scheduling: An update. European Journal of Operational Research, 174(1), 23–37. doi:10.1016/j.ejor.2005.01.065
- Lambrechts, O., Demeulemeester, E., & Herroelen, W. (2008). A tabu search procedure for developing robust predictive project schedules. International Journal of Production Economics, 111(2), 493–508. doi:10.1016/j.ijpe.2007.02.003
- Li, K. Y., & Willis, R. J. (1992). An iterative scheduling technique for resource-constrained project scheduling. European Journal of Operational Research, 56(3), 370–379. doi:10.1016/0377-2217(92)90320-9
- Loxton, R., & Mardaneh, E. (2020). Random data for testing a maintenance optimization algorithm. http://dx.doi.org/10.25917/5e1feb1386c72
- Megow, N., Mohring, R. H., & Schulz, J. (2011). Decision support and optimization in shutdown and turnaround scheduling. INFORMS Journal on Computing, 23(2), 189–204. doi:10.1287/ijoc.1100.0393
- Mika, M., Waligóra, G., & Wȩglarz, J. (2015). Overview and state of the art. In Christoph Schmidt & Jürgen Zimmermann (eds.), Handbook on project management and scheduling (Vol. 1, pp. 445–490). Springer.
- Moinian, F., Sabouhi, H., Hushmand, J., Hallaj, A., Khaledi, H., & Mohammadpour, M. (2017). Gas turbine preventive maintenance optimization using genetic algorithm. International Journal of System Assurance Engineering and Management, 8(3), 594–601. doi:10.1007/s13198-017-0627-3
- Pellerin, R., Perrier, N., & Berthaut, F. (2020). A survey of hybrid metaheuristics for the resource-constrained project scheduling problem. European Journal of Operational Research, 280(2), 395–416. doi:10.1016/j.ejor.2019.01.063
- Pillac, V., Guéret, C., & Medaglia, A. L. (2013). A parallel matheuristic for the technician routing and scheduling problem. Optimization Letters, 7(7), 1525–1535. doi:10.1007/s11590-012-0567-4
- Ranjbar, M., Khalilzadeh, M., Kianfar, F., & Etminani, K. (2012). An optimal procedure for minimizing total weighted resource tardiness penalty costs in the resource-constrained project scheduling problem. Computers & Industrial Engineering, 62(1), 264–270. doi:10.1016/j.cie.2011.09.013
- Sankararaman, S. (2015). Significance, interpretation, and quantification of uncertainty in prognostics and remaining useful life prediction. Mechanical Systems and Signal Processing, 52-53(1), 228–247. doi:10.1016/j.ymssp.2014.05.029
- Shi, H., & Zeng, J. (2016). Real-time prediction of remaining useful life and preventive opportunistic maintenance strategy for multi-component systems considering stochastic dependence. Computers & Industrial Engineering, 93, 192–204. doi:10.1016/j.cie.2015.12.016
- Shim, S. O., & Kim, Y. D. (2007). Scheduling on parallel identical machines to minimize total tardiness. European Journal of Operational Research, 177(1), 135–146. doi:10.1016/j.ejor.2005.09.038
- Sprecher, A. (2000). Scheduling resource-constrained projects competitively at modest memory requirements. Management Science, 46(5), 710–723. doi:10.1287/mnsc.46.5.710.12044
- Yoosefzadeh, H. R., & Tareghian, H. R. (2013). Hybrid solution method for resource-constrained project scheduling problem using a new schedule generator. The International Journal of Advanced Manufacturing Technology, 66(5-8), 1171–1180. doi:10.1007/s00170-012-4398-3
- Zamorano, E., & Stolletz, R. (2017). Branch-and-price approaches for the multiperiod technician routing and scheduling problem. European Journal of Operational Research, 257(1), 55–68. doi:10.1016/j.ejor.2016.06.058
- Ziarati, K., Akbari, R., & Zeighami, V. (2011). On the performance of bee algorithms for resource-constrained project scheduling problem. Applied Soft Computing, 11(4), 3720–3733. doi:10.1016/j.asoc.2011.02.002