Towards Efficient Ship Design: A Review of Methods and Attributes for Decision-Making in Ship Selection
DOI:
https://doi.org/10.31181/dmame8220251580Keywords:
Ship Selection, MCDM, Life Cycle Analysis, System Engineering, Sustainable Naval DesignAbstract
With the increasing sophistication of naval systems and the rising imperative for environmentally sustainable solutions, it becomes crucial to understand how multi-criteria decision-making (MCDM) models facilitate informed decision-making to ensure vessel performance and sustainability throughout their life cycle. This research undertakes a systematic literature review of MCDM applications across various stages of the ship life cycle from a systems engineering standpoint. Particular attention is given to the design phase, where MCDM approaches are employed to determine the most appropriate ship configuration, considering factors such as operational capabilities, effectiveness, and performance metrics. A total of 131 studies were examined following the PRISMA methodology, with data sourced from Scopus and the Web of Science. The review concentrated on design methodologies, hierarchical structuring, and the assessment of essential decision-making criteria, including cost, effectiveness, and risk. The results demonstrate that MCDM models not only support the identification of optimal ship configurations but also assist in evaluating their effects on operational efficiency and environmental sustainability. The study underscores the importance of incorporating a range of performance measures, including Measures of Effectiveness (MOE), Measures of Performance (MOPs), Technical Performance Measures (TPMs), and Key Performance Parameters (KPPs), to strengthen decision-making in both design and operational contexts. Finally, a framework is proposed to guide the selection of vessels that are both operationally efficient and environmentally compliant, in line with contemporary regulatory requirements.
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[1] AAP, N. S. (2015). 20/NATO Programme Management Framework (NATO Life Cycle Model). Edition C Version, 1. https://tssodyp.ssb.gov.tr/genel/ReferansDokumanlar/AAP-20-2015.pdf
[2] Aikhuele, D. O., & Turan, F. M. (2018). A modified exponential score function for troubleshooting an improved locally made Offshore Patrol Boat engine. Journal of marine engineering & technology, 17(1), 52-58. https://doi.org/10.1080/20464177.2017.1286841
[3] Amaral, P. H. A. S. d. (2019). Aplicação do suporte de logística integrado, ILS sx000i, nos procedimentos de manutenção em companhias aéreas.
[4] Andrews, D. (1998). A comprehensive methodology for the design of ships (and other complex systems). Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 454(1968), 187-211. https://doi.org/10.1098/rspa.1998.0154
[5] Erikstad, S. O., & Lagemann, B. (2022, June). Design methodology state-of-the-art report. In SNAME International Marine Design Conference (p. D031S000R001). SNAME. https://doi.org/10.5957/IMDC-2022-301
[6] Animah, I., Addy-Lamptey, A., Korsah, F., & Sackey, J. S. (2018). Compliance with MARPOL Annex VI regulation 14 by ships in the Gulf of Guinea sub-region: Issues, challenges and opportunities. Transportation Research Part D: Transport and Environment, 62, 441-455. https://doi.org/10.1016/j.trd.2018.03.020
[7] Arce, M. E., Saavedra, Á., Míguez, J. L., & Granada, E. (2015). The use of grey-based methods in multi-criteria decision analysis for the evaluation of sustainable energy systems: A review. Renewable and Sustainable Energy Reviews, 47, 924-932. https://doi.org/10.1016/j.rser.2015.03.010
[8] Aspen, D. M., Sparrevik, M., & Fet, A. M. (2015). Review of methods for sustainability appraisals in ship acquisition. Environment Systems and Decisions, 35(3), 323-333. https://doi.org/10.1007/s10669-015-9561-6
[9] Balin, A., Demirel, H., & Alarcin, F. (2016). A novel hybrid MCDM model based on fuzzy AHP and fuzzy TOPSIS for the most affected gas turbine component selection by the failures. Journal of marine engineering & technology, 15(2), 69-78. https://doi.org/10.1080/20464177.2016.1216252
[10] Balin, A., Şener, B., & Demirel, H. (2019). An integrated fuzzy mcdm model for evaluation and selection of a suitable tugboat. International Journal of Maritime Engineering, 161(A3). https://doi.org/10.5750/ijme.v161iA3.1097
[11] Beşikçi, E. B., Kececi, T., Arslan, O., & Turan, O. (2016). An application of fuzzy-AHP to ship operational energy efficiency measures. Ocean Engineering, 121, 392-402. https://doi.org/10.1016/j.oceaneng.2016.05.031
[12] Blagojević, B., Jonsson, R., Björheden, R., Nordström, E.-M., & Lindroos, O. (2019). Multi-criteria decision analysis (MCDA) in forest operations–an introductional review. Croatian Journal of Forest Engineering: Journal for Theory and Application of Forestry Engineering, 40(1), 191-2015. https://hrcak.srce.hr/217409
[13] Bottero, M., & Gualeni, P. (2024). Systems engineering for naval ship design evolution. Journal of Marine Science and Engineering, 12(2), 210. https://doi.org/10.3390/jmse12020210
[14] Brewer, E., Demmer, M., Du, B., Ho, M., Kam, M., Nedevschi, S., Pal, J., Patra, R., Surana, S., & Fall, K. (2005). The case for technology in developing regions. Computer, 38(6), 25-38. https://doi.org/10.1109/MC.2005.204
[15] Bui, K. Q., & Perera, L. P. (2019). The compliance challenges in emissions control regulations to reduce air pollution from shipping. OCEANS 2019-Marseille, 1728114500. https://doi.org/10.1109/OCEANSE.2019.8867420
[16] Carmona, D. H. (2011). Teoría General de Sistemas: un enfoque hacia la ingeniería de sistemas 2Ed. Lulu. com. https://www.amazon.com/-/es/Teor%C3%ADa-General-Sistemas-ingenier%C3%ADa-sistemas/dp/1257781936
[17] Cheemakurthy, H., & Garme, K. (2022). Fuzzy AHP-based design performance index for evaluation of ferries. Sustainability, 14(6), 3680. https://doi.org/10.3390/su14063680
[18] Chewning, I., & Moretto, S. (2000). Advances in Aircraft Carrier Life Cycle Cost Analysis for Acquisition and Ownership Decision‐Making. Naval Engineers Journal, 112(3), 97-110. https://doi.org/10.1111/j.1559-3584.2000.tb03308.x
[19] Dang, R., Li, X., Li, C., & Xu, C. (2021). A MCDM framework for site selection of island photovoltaic charging station based on new criteria identification and a hybrid fuzzy approach. Sustainable Cities and Society, 74, 103230. https://doi.org/10.1016/j.scs.2021.103230
[20] Dos Santos, M., de Araújo Costa, I. P., & Gomes, C. F. S. (2021). Multicriteria decision-making in the selection of warships: a new approach to the AHP method. International Journal of the Analytic Hierarchy Process, 13(1). https://doi.org/10.13033/ijahp.v13i1.833
[21] Dot, U. (2007). Systems engineering for intelligent transportation systems. Federal Highway Administration & Federal Transit Administration. https://ops.fhwa.dot.gov/seits/files/segbv4rem.pdf
[22] Dávila, C. A. C. (2021). Criterios y métodos para seleccionar la ubicación de los rellenos sanitarios. Revista de Investigación de Agroproducción Sustentable, 5(2), 9-19. https://doi.org/10.25127/aps.20212.764
[23] Emovon, I., Norman, R. A., & Murphy, A. J. (2018). Hybrid MCDM based methodology for selecting the optimum maintenance strategy for ship machinery systems. Journal of intelligent manufacturing, 29(3), 519-531. https://doi.org/10.1007/s10845-015-1133-6
[24] Eski, S., & Özaslan, İ. H. (2022). The Effect of Integrated Logistics Support System on Life Cycle Management. Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty, 9(2), 940-972. https://doi.org/10.30798/makuiibf.914006
[25] Española, R. A. (2025). Embarcación. https://dle.rae.es/embarcaci%C3%B3n
[26] Fernandez, C., Dev, A. K., Norman, R., Woo, W. L., & Kumar, S. B. (2019). Dynamic Positioning System: Systematic Weight Assignment for DP Sub-Systems Using Multi-Criteria Evaluation Technique Analytic Hierarchy Process and Validation Using DP-RI Tool With Deep Learning Algorithm. International Conference on Offshore Mechanics and Arctic Engineering, 0791858766. https://doi.org/10.1115/OMAE2019-95485
[27] Fiskin, R. (2023). An advanced decision-making model for determining ship domain size with a combination of MCDM and fuzzy logic. Ocean Engineering, 283, 114976. https://doi.org/10.1016/j.oceaneng.2023.114976
[28] Galdo, M. I. L., Miranda, J. T., Lorenzo, J. M. R., & Caccia, C. G. (2021). Internal modifications to optimize pollution and emissions of internal combustion engines through multiple-criteria decision-making and artificial neural networks. International Journal of Environmental Research and Public Health, 18(23), 12823. https://doi.org/10.3390/ijerph182312823
[29] Gebre, S. L., Cattrysse, D., Alemayehu, E., & Van Orshoven, J. (2021). Multi-criteria decision making methods to address rural land allocation problems: A systematic review. International Soil and Water Conservation Research, 9(4), 490-501. https://doi.org/10.1016/j.iswcr.2021.04.005
[30] Godás, L. (2006). El ciclo de vida del producto. Offarm, 25(8), 11-142. https://gc.scalahed.com/recursos/files/r161r/w24792w/TV/GODAS_ciclo.pdf
[31] Görçün, Ö. F. (2022). A novel integrated MCDM framework based on Type-2 neutrosophic fuzzy sets (T2NN) for the selection of proper Second-Hand chemical tankers. Transportation Research Part E: Logistics and Transportation Review, 163, 102765. https://doi.org/10.1016/j.tre.2022.102765
[32] Görçün, Ö. F., Kundu, P., Küçükönder, H., & Senthil, S. (2024). Evaluation of the second-hand LNG tanker vessels using fuzzy MCGDM approach based on the Interval type-2 fuzzy ARAS (IT2F–ARAS) technique. Ocean Engineering, 303, 117788. https://doi.org/10.1016/j.oceaneng.2024.117788
[33] Hermann, R. R., & Wigger, K. (2017). Eco-innovation drivers in value-creating networks: A case study of ship retrofitting services. Sustainability, 9(5), 733. https://doi.org/10.3390/su9050733
[34] Hootman, J. C., & Whitcomb, C. (2005). A military effectiveness analysis and decision making framework for naval ship design and acquisition. Naval Engineers Journal, 117(3), 43-61. https://doi.org/10.1111/j.1559-3584.2005.tb00360.x
[35] Hsu, Y.-C., Lu, H.-A., & Chu, C.-W. (2016). Evaluating and selecting maritime suppliers. Maritime Policy & Management, 43(1), 39-58. https://doi.org/10.1080/03088839.2015.1035351
[36] INCOSE. (2023). INCOSE systems engineering handbook. John Wiley & Sons. https://www.wiley.com/en-us/INCOSE+Systems+Engineering+Handbook%2C+5th+Edition-p-9781119814290
[37] Jafaryeganeh, H., Ventura, M., & Soares, C. G. (2020). Application of multi-criteria decision making methods for selection of ship internal layout design from a Pareto optimal set. Ocean Engineering, 202, 107151. https://doi.org/10.1016/j.oceaneng.2020.107151
[38] Kabashkin, I., & Zvaigzne, A. (2018). Multi Criteria Decision Making in Life Cycle Management of Modular Ships with Test System. International Conference on Reliability and Statistics in Transportation and Communication, 273-283. https://doi.org/10.1007/978-3-319-74454-4_26
[39] Karakoç, Ö., Memiş, S., & Sennaroglu, B. (2023). A review of sustainable supplier selection with decision-making methods from 2018 to 2022. Sustainability, 16(1), 125. https://doi.org/10.3390/su16010125
[40] Keen, P. G. (1976). The evolving concept of optimality. Graduate School of Business, Stanford University. https://www.gsb.stanford.edu/faculty-research/working-papers/evolving-concept-optimality
[41] Keyghobadi, M., Shahabi, S. H. R., & Seif, M. (2020). Application of MCDM methods in managerial decisions for identifying and evaluating future options: A real case study in shipbuilding industry. Journal of Industrial and Systems Engineering, 13(1), 262-286. https://dor.isc.ac/dor/20.1001.1.17358272.2020.13.1.13.7
[42] Kossiakoff, A., Seymour, S. J., Flanigan, D. A., & Biemer, S. M. (2011). Systems Engineering Principles and Practice. https://doi.org/10.1002/9781119516699
[43] Kristensen, H. S., & Mosgaard, M. A. (2020). A review of micro level indicators for a circular economy–moving away from the three dimensions of sustainability? Journal of Cleaner Production, 243, 118531. https://doi.org/10.1016/j.jclepro.2019.118531
[44] Kumar, U. D., & Crocker, J. (2012). Reliability, maintenance and logistic support:-A life cycle approach. Springer Science & Business Media. https://doi.org/10.1007/978-1-4615-4655-9
[45] Kuper, A. (2008). Adquisición de un buque de carga Universidad de Buenos Aires. Facultad de Ciencias Económicas.]. http://bibliotecadigital.econ.uba.ar/download/tpos/1502-0442_KuperA.pdf
[46] Kuroshi, L., & Ölçer, A. (2017). Technique selection and evaluation of ballast water management methods under an intuitionistic fuzzy environment: An information axiom approach. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 231(3), 782-800. https://doi.org/10.1177/1475090216674543
[47] Lambert, K. R. (2017). Supporting high-technology systems during periods of extended life-cycles by means of integrated logistics support. South African Journal of Industrial Engineering, 28(1), 125-132. https://doi.org/10.7166/28-1-1455
[48] Lameira, P. I. D., Filgueiras, T. C. G. M., Botter, R. C., & dos Santos Saavedra, R. (2020). An approach using multicriteria decision methods to barges configuration for pushed convoys in the Amazon. International Journal of Information Technology & Decision Making, 19(01), 317-341. https://doi.org/10.1142/S0219622019500482
[49] Linkov, I., Loney, D., Cormier, S., Satterstrom, F. K., & Bridges, T. (2009). Weight-of-evidence evaluation in environmental assessment: review of qualitative and quantitative approaches. Science of the Total Environment, 407(19), 5199-5205. https://doi.org/10.1016/j.scitotenv.2009.05.004
[50] Liu, X., Tian, G., Fathollahi-Fard, A. M., & Mojtahedi, M. (2020). Evaluation of ship’s green degree using a novel hybrid approach combining group fuzzy entropy and cloud technique for the order of preference by similarity to the ideal solution theory. Clean Technologies and Environmental Policy, 22(2), 493-512. https://doi.org/10.1007/s10098-019-01798-7
[51] Golany, B., & Kress, M. (2020). Measuring readiness and sustainment within analysis of alternatives in military systems acquisition. Military Operations Research, 25(4), 63-77. https://www.jstor.org/stable/26957616
[52] Liu, Z., Lin, Y., & Ji, Z. (2009). Life-cycle based risk evaluation for ship project. ISOPE International Ocean and Polar Engineering Conference, https://onepetro.org/ISOPEIOPEC/proceedings-abstract/ISOPE09/All-ISOPE09/7708
[53] Ma, W., Du, Y., Liu, X., & Shen, Y. (2022). Literature review: Multi-criteria decision-making method application for sustainable deep-sea mining transport plans. Ecological Indicators, 140, 109049. https://doi.org/10.1016/j.ecolind.2022.109049
[54] Maceiras, R., Alfonsin, V., Alvarez-Feijoo, M. A., & Llopis, L. (2023). Assessment of Selected Alternative Fuels for Spanish Navy Ships According to Multi-Criteria Decision Analysis. Journal of Marine Science and Engineering, 12(1), 77. https://doi.org/10.3390/jmse12010077
[55] Madi, E., Naim, S., Yaafar, A., Yaakob, A., & Yusoff, B. (2020). Agreement matrix based on fuzzy decision-making to rank ship Berthing criteria. International Journal of Engineering Trends and Technology, 68(12), 31-36. https://doi.org/10.14445/22315381/IJETT-V68I12P206
[56] Malyszko, M. (2021). Fuzzy logic in selection of maritime search and rescue units. Applied Sciences, 12(1), 21. https://doi.org/10.3390/app12010021
[57] Manap, N., & Voulvoulis, N. (2015). Environmental management for dredging sediments–The requirement of developing nations. Journal of environmental management, 147, 338-348. https://doi.org/10.1016/j.jenvman.2014.09.024
[58] Martins, M. R., & Burgos, D. F. (2008). Multi-objective optimization technique applied to preliminary design of a tanker. International Conference on Offshore Mechanics and Arctic Engineering, 409-417. https://doi.org/10.1115/OMAE2008-57441
[59] Matulja, T., Bogdanović, M., & Udovičić, N. (2013). Selection of the Racing Multihull Sailing Boat Equipment by the AHP Method–A Case Study. Pomorstvo, 27(2), 313-324. https://hrcak.srce.hr/112526
[60] McWhite, J. (2000). CVNX—expanded capability baseline aircraft carrier design study. Naval Engineers Journal, 112(3), 47-57. https://doi.org/10.1111/j.1559-3584.2000.tb03303.x
[61] Mohamed, B. H., Belkadi, M., Aounallah, M., & Adjlout, L. (2023). Multi-Objective Design Optimization of Bulk Carriers. Journal of Naval Architecture & Marine Engineering, 20(2). https://doi.org/10.3329/jname.v20i2.66373
[62] Mohamed, R., Ghazali, M., & Samsudin, M. A. (2020). A systematic review on mathematical language learning using PRISMA in Scopus database. Eurasia Journal of Mathematics, Science and Technology Education, 16(8), em1868. https://doi.org/10.29333/ejmste/8300
[63] Morris, B., Cook, S., & Cannon, S. (2018). A Methodology to Support Early Stage Off-the-Shelf Naval Vessel Acquisitions. International Journal of Maritime Engineering, 160(A1). https://doi.org/10.5750/ijme.v160iA1.1045
[64] Morris, P. W., & Pinto, J. K. (2007). The Wiley guide to project technology, supply chain, and procurement management. John Wiley & Sons. 047022682X. https://www.wiley.com/en-nl/The+Wiley+Guide+to+Project+Technology%2C+Supply+Chain%2C+and+Procurement+Management-p-9780470226827
[65] Moshiul, A. M., Mohammad, R., Hira, F. A., & Maarop, N. (2022). Alternative marine fuel research advances and future trends: A bibliometric knowledge mapping approach. Sustainability, 14(9), 4947. https://doi.org/10.3390/su14094947
[66] Nayak, S. (2020). Fundamentals of optimization techniques with algorithms. Academic Press. https://cir.nii.ac.jp/crid/1971993809766198679
[67] Ölçer, A., Tuzcu, C., & Turan, O. (2006). An integrated multi-objective optimisation and fuzzy multi-attributive group decision-making technique for subdivision arrangement of Ro–Ro vessels. Applied Soft Computing, 6(3), 221-243. https://doi.org/10.1016/j.asoc.2005.01.004
[68] Ortiz Buitrago, V., & Pardo López, H. F. (2021). Importancia y ventajas de los KPI (Key Performance Indicators) en los proyectos: enfoque de procesos en el sector petrolero. https://repository.upb.edu.co/handle/20.500.11912/9609
[69] Osezua-Aikhuele, D., Sorooshian, S., Hannis-Ansah, R., & Mohd-Turan, F. (2017). Application of intuitionistic fuzzy topsis model for troubleshooting an offshore patrol boat engine. Polish Maritime Research(2), 68-76. https://doi.org/10.1515/pomr-2017-0051
[70] Özdemir, Ü., Yılmaz, H., & Başar, E. (2015). Determination of marine pollution caused by ship operations using the DEMATEL method. 11th International Conference Transnav, 17-19. https://doi.org/10.1201/b18514-34
[71] Office of Aerospace Studies. Analysis of Alternatives (AoA) Handbook: A Practical Guide to the Analysis of Alternatives. Headquarters Air Force (HAF/A5RA-OAS), Washington, DC, 4 August 2017. https://afacpo.com/AQDocs/AoAHandbook.pdf
[72] Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., & Brennan, S. E. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. bmj, 372. https://doi.org/10.1136/bmj.n71
[73] Page, M. J., & Moher, D. (2017). Evaluations of the uptake and impact of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Statement and extensions: a scoping review. Systematic reviews, 6(1), 263. https://doi.org/10.1186/s13643-017-0663-8
[74] Pal, M. (2015). Ship work breakdown structures through different ship lifecycle stages. International conference on computer applications in shipbuilding, https://apps.dtic.mil/sti/html/tr/ADA052119/
[75] Papanikolaou, A., Zaraphonitis, G., Boulougouris, E., Langbecker, B., Matho, S., & Sames, P. (2011). Optimization of oil outflow and cargo capacity of an AFRAMAX oil tanker design. https://dspace.lib.ntua.gr/xmlui/handle/123456789/36297
[76] Papanikolaou, A., Zaraphonitis, G., Boulougouris, E., Langbecker, U., Matho, S., & Sames, P. (2010). Multi-objective optimization of oil tanker design. Journal of Marine Science and Technology, 15(4), 359-373. https://doi.org/10.1007/s00773-010-0097-7
[77] Raber, J., & Perin, D. (2000). Future USN aircraft carrier Analysis of alternatives. Naval Engineers Journal, 112(3), 15-25. https://doi.org/10.1111/j.1559-3584.2000.tb03300.x
[78] Rains, D. A. (1999). Fleet mix mission effectiveness analysis. Naval Engineers Journal, 111(1), 65-81. https://doi.org/10.1111/j.1559-3584.1999.tb01220.x
[79] Rodríguez, B. R. (2003). El análisis del ciclo de vida y la gestión ambiental. Boletin IiE, 91-97. https://www.ucipfg.com/Repositorio/MAES/MAES-07/BLOQUE-ACADEMICO/Unidad-3/lecturas/ACV_GA.pdf
[80] Sahin, B., Yip, T. L., Tseng, P.-H., Kabak, M., & Soylu, A. (2020). An application of a fuzzy TOPSIS multi-criteria decision analysis algorithm for dry bulk carrier selection. Information, 11(5), 251. https://doi.org/10.3390/info11050251
[81] Sanders, A., & Klein, J. (2012). Systems engineering framework for integrated product and industrial design including trade study optimization. Procedia Computer Science, 8, 413-419. https://doi.org/10.1016/j.procs.2012.01.080
[82] Simon, H. A. (1956). Rational choice and the structure of the environment. Psychological review, 63(2), 129. https://psycnet.apa.org/doi/10.1037/h0042769
[83] U.S. Air Force. AF/A5/7 Capability Development Guidebook Vol.2D Annex A. Analysis of Alternatives (AoA). Washington, DC, USA, Dec. 2023. https://www.afacpo.com/AQDocs/A57_Capability_Development_Guidebook_Vol2DAnnexA.pdf
[84] Smirlis, Y. G., & Bonazountas, M. (2020). A Composite Indicators Approach to Assisting Decisions in Ship LCA/LCC. ICORES, https://www.scitepress.org/Papers/2020/88954/88954.pdf
[85] Stepanchick, J., & Brown, A. (2007). Revisiting DDGX/DDG‐51 concept exploration. Naval Engineers Journal, 119(3), 67-88. https://doi.org/10.1111/j.1559-3584.2007.00069.x
[86] Sulligoi, G., Trincas, G., Vicenzutti, A., Braidotti, L., & Cataneo, M. (2021). Concept Design Methodology to Enable Naval Smart Grid onboard Electric Ships. 2021 IEEE Electric Ship Technologies Symposium (ESTS), 1728184266. https://doi.org/10.1109/ESTS49166.2021.9512322
[87] Uğurlu, Ö. (2015). Application of Fuzzy Extended AHP methodology for selection of ideal ship for oceangoing watchkeeping officers. International Journal of Industrial Ergonomics, 47, 132-140. https://doi.org/10.1016/j.ergon.2015.01.013
[88] Vakili, S., Ölcer, A. I., & Ballini, F. (2020). The trade-off analysis for the mitigation of underwater noise pollution from commercial vessels: case study–Trans Mountain project, Port of Vancouver, Canada. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 234(2), 599-617. https://doi.org/10.1177/1475090219886397
[89] Vaskić, L., & Paetzold, K. (2019). The system life cycle turbine: A proposal for a universal system life cycle model in aerospace and defense. 2019 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), 1728134013. https://doi.org/10.1109/ICE.2019.8792682
[90] Wan, C., Yan, X., Zhang, D., & Yang, Z. (2019). A novel policy making aid model for the development of LNG fuelled ships. Transportation Research Part A: Policy and Practice, 119, 29-44. https://doi.org/10.1016/j.tra.2018.10.038
[91] Wang, X., Tian, M., Chen, X., Xie, P., Yang, J., Chen, J., & Yang, W. (2022). Advances on materials design and manufacture technology of plastic liner of type Ⅳ hydrogen storage vessel. International journal of hydrogen energy, 47(13), 8382-8408. https://doi.org/10.1016/j.ijhydene.2021.12.198
[92] Yang, Z., Bonsall, S., & Wang, J. (2011). Approximate TOPSIS for vessel selection under uncertain environment. Expert Systems with Applications, 38(12), 14523-14534. https://doi.org/10.1177/1475090219886397
[93] Yang, Z., Maistralis, L., Bonsall, S., & Wang, J. (2017). Use of fuzzy evidential reasoning for vessel selection under uncertainty. In Multi-Criteria Decision Making in Maritime Studies and Logistics: Applications and Cases (pp. 105-121). Springer. https://doi.org/10.1007/978-3-319-62338-2_5
[94] Yang, Z., Mastralis, L., Bonsall, S., & Wang, J. (2009). Incorporating uncertainty and multiple criteria in vessel selection. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 223(2), 177-188. https://doi.org/10.1243/14750902JEME129
[95] Žanić, V., Andrić, J., Prebeg, P., Stipčević, M., & Pirić, K. (2010). RoPax structural design-multi-level decision support methodology. Proceedings of PRADS 2010. https://www.croris.hr/crosbi/publikacija/prilog-skup/562137
[96] Yazır, D., Şahin, B., & Yip, T. L. (2021). Selection of new design gas carriers by using fuzzy EVAMIX method. The Asian Journal of Shipping and Logistics, 37(1), 91-104. https://doi.org/10.1016/j.ajsl.2020.10.001
[97] Zanic, V., Andric, J., & Prebeg, P. (2009). Design environment for structural design: application to modern multideck ships. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 223(1), 105-120. https://doi.org/10.1243/14750902JEME108
[98] Zanic, V., Andric, J., & Prebeg, P. (2013). Design synthesis of complex ship structures. Ships and offshore Structures, 8(3-4), 383-403. https://doi.org/10.1080/17445302.2013.783455
[99] Zanic, V., & Čudina, P. (2009). Multiattribute decision making methodology in the concept design of tankers and bulk carriers. Brodogradnja: An International Journal of Naval Architecture and Ocean Engineering for Research and Development, 60(1), 19-43. https://hrcak.srce.hr/file/54869
[100] Pal, M. (2015). Ship work breakdown structures through different ship lifecycle stages. In International conference on computer applications in shipbuilding. https://www.academia.edu/23487106
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