[
1. P. Bzura. ‘Diagnostic model of crankshaft seals’. Polish Maritime Research. 2019, Vol. 26, Issue: 3, 39-46.10.2478/pomr-2019-0044
]Search in Google Scholar
[
2. A. Krystosik-Gromadzinska, W. Zenczak. ‘Improvements to a fire safety management system’. Polish Maritime Research. 2019, Vol. 26, Issue 4, 117-123.10.2478/pomr-2019-0073
]Search in Google Scholar
[
3. Ch. Gong, D. M. Frangpol, M. Cheng. ‘Risk-based life-cycle optimal dry-docking inspection of corroding ship hull tankers’. Engineering Structures. 2019, 195, 559-567.10.1016/j.engstruct.2019.05.063
]Search in Google Scholar
[
4. J. Girtler. ‘Limiting distribution of the three-state semi-markov model of technical state transitions of ship power plant machines and its applicability in operational decision-making’. Polish Maritime Research. 2020, Vol. 27, Issue: 2, 136-144.10.2478/pomr-2020-0035
]Search in Google Scholar
[
5. S. Wu, Y. Chen, Q. Wu, Z. Wang. ‘Linking component importance to optimisation of preventive maintenance policy’. Reliability Engineering and System Safety. 2016, 146, 26-32.10.1016/j.ress.2015.10.008
]Search in Google Scholar
[
6. D. Butler. ‘A Guide to Ship Repair Estimates in Man-hours’. 2012, DOI: 10710.1016/B978-0-08-098262-5.00008-18.
]Search in Google Scholar
[
7. S. Muthia, Naffisah, I. Surjandari, A. Rachman, R.W.H. Palupi, ‘Estimation of Dry Docking Maintenance Duration using Artificial Neural Network’. Int Journal of Computing, Communications & Instrumentation Engg. 2014, Vol. 1, Issue 1, 2349-1477.
]Search in Google Scholar
[
8. I. Surjandari, R. Novita. ‘Estimation Model of Dry Docking Duration Using Data Mining’. World Academy of Science, Engineering and Technology. 2013, Vol. 7.
]Search in Google Scholar
[
9. E. Manea, M-G. Manea, ‘The Influence of the Deadweight in the Projection of the Duration of the Maritime Ships Mentenancy Works’, Advanced Engineering Forum 2019, 34, 292-299.10.4028/www.scientific.net/AEF.34.292
]Search in Google Scholar
[
10. K. A. Dev, M. Saha. ‘Modelling and Analysis of Ship Repairing Time’. Journal of Ship Production and Design. 2015, Vol. 31, No. 1, 1-8.10.5957/jspd.2015.31.2.129
]Search in Google Scholar
[
11. W. Tarełko.’Control model of maintainability level’. Reliability Engineering and System Safety. 1995, 47, 85-91.10.1016/0951-8320(94)00055-S
]Search in Google Scholar
[
12. Z. Bouayed, Ch.E. Penney, A. Sokri, T. Yazeck, ‘Estimating Maintenance Costs for Royal Canadian Navy Ships’, Scientific Report DRDC-RDDC-2017-R147.
]Search in Google Scholar
[
13. J.E.C. Arroyo, V. A. Armentano. ‘Genetic local search for multi-objective flowshop scheduling problems’. European journal of operational research. 2005, 167, 717-738.10.1016/j.ejor.2004.07.017
]Search in Google Scholar
[
14. X. Cai, K. N. Li. ‘A genetic algorithm for scheduling staff of mixed skills under multi-criteria’. European Journal of Operational Research. 2000, 125, 359-369.10.1016/S0377-2217(99)00391-4
]Search in Google Scholar
[
15. G. Cavory, R. Dupas, G. Goncalves. ‘A genetic approach to solving the problem of cyclic job shop scheduling with linear constraints’. European Journal of Operational Research. 2005, 161, 73-85.10.1016/j.ejor.2003.03.001
]Search in Google Scholar
[
16. I. Paprocka, C. Grabowik, W.M. Kempa, D. Krenczyk, K. Kalinowski. ‘The influence of algorithms for basic-schedule generation on the performance of predictive and reactive schedules’. Conf. Series: Materials Science and Engineering. 2018, 400, 1757-8981, DOI:10.1088/1757-899X/400/2/022042.10.1088/1757-899X/400/2/022042
]Search in Google Scholar
[
17. S. Bertel, J.-C. Billaut. ‘A genetic algorithm for an industrial multiprocessor flow shop scheduling problem with recirculation’. European Journal of Operational Research. 2004, 159, 651-662.10.1016/S0377-2217(03)00434-X
]Search in Google Scholar
[
18. [18] M.E. Kurz, R.G. Askin. ‘Scheduling flexible flow lines with sequence-dependent setup times’. European Journal of Operational Research. 2004, 159, 66-82.10.1016/S0377-2217(03)00401-6
]Search in Google Scholar
[
19. R. Cheng, M. Gen, Y. Tsujimura. ‘A tutorial survey of job-shop scheduling problems using genetic algorithms, part II: hybrid genetic search strategies’, Computers & Industrial Engineering. 1999, 36, 343-346.10.1016/S0360-8352(99)00136-9
]Search in Google Scholar
[
20. J. F. Goncalves, J. J. de M. Mendes, M. G. C. Resende. ‘A hybrid genetic algorithm for the job shop scheduling problem’. European Journal of Operational Research. 2005, 167, 77-95.10.1016/j.ejor.2004.03.012
]Search in Google Scholar
