174 119
Full Length Article
American Journal of Business and Operations Research
Volume 7 , Issue 2, PP: 08-18 , 2022 | Cite this article as | XML | Html |PDF


An Innovative Multi-Criteria Decision-Making (MCDM) Framework for Picking the Right Used Chemical Tankers: A Classified Model-Based Discussion

Authors Names :   Abedallah Z. Abualkishik   1 *     Rasha Almajed   2     William Thompson   3  

1  Affiliation :  American University in the Emirates, Dubai, UAE

    Email :  abedallah.abualkishik@aue.ae

2  Affiliation :  American University in the Emirates, Dubai, UAE

    Email :  rasha.almajed@aue.ae

3  Affiliation :  Towson University, Towson University, Maryland's University, USA

    Email :  wvthompson@towson.edu

Doi   :   https://doi.org/10.54216/AJBOR.070201

Received: April 03, 2022 Accepted: August 22, 2022

Abstract :

Because chemical tanker boats are so expensive to build and maintain, shipping firms may not be able to supply their clients with fair transportation pricing. As a result, shipping businesses may find various benefits and chances by purchasing second-hand chemical tanker vessels. But picking a chemical tanker is a hard task that requires overcoming numerous misunderstandings and weighing several conflicting factors.  A novel MCDM technique has been proposed in this study for this aim. EDAS approach is used in the proposed model, to handle uncertainty. In order to demonstrate efficacy, relevance, and robustness, the model was used to address decision-making issues involving the selection of suitable second-hand chemical tankers from a pool of 10 (alternatives). The chemical tanker boats were evaluated using 14 distinct choice criteria in the present article. The findings show that the most important factor is "CTC6′′ Maintenance cost," and the best and most preferred chemical tanker is "CTA6"

Keywords :

MCDM; Chemical tankers; EDAS; Maritime Industry; Transportation; Shipping firms

References :

[1]         A. Schmidt, L. Uhlenbrock, and J. Strube, “Technical Potential for Energy and GWP Reduction in Chemical–Pharmaceutical Industry in Germany and EU—Focused on Biologics and Botanicals Manufacturing,” Processes, vol. 8, no. 7, p. 818, 2020.

[2]         Ö. F. Görçün, “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, vol. 163, p. 102765, 2022.

[3]         L. Carballo Piñeiro, M. Q. Mejia, and F. Ballini, “Beyond COVID-19: the future of maritime transport,” WMU Journal of Maritime Affairs, vol. 20, no. 2, pp. 127–133, 2021.

[4]         M. Stopford, Maritime economics 3e. Routledge, 2008.


[6]         L. Fan, B. Gu, and J. Yin, “Investment incentive analysis for second-hand vessels,” Transport Policy, vol. 106, pp. 215–225, 2021.

[7]         K.-S. Park, Y.-J. Seo, A.-R. Kim, and M.-H. Ha, “Ship acquisition of shipping companies by sale & purchase activities for sustainable growth: Exploratory fuzzy-AHP application,” Sustainability, vol. 10, no. 6, p. 1763, 2018.

[8]         A. S. Jetlund and I. A. Karimi, “Improving the logistics of multi-compartment chemical tankers,” Computers & Chemical Engineering, vol. 28, no. 8, pp. 1267–1283, 2004.

[9]         D. Gavalas, T. Syriopoulos, and M. Tsatsaronis, “Assessing key performance indicators in the shipbuilding industry; an MCDM approach,” Maritime Policy & Management, pp. 1–29, 2021.

[10]       M. dos Santos, I. P. de Araujo Costa, and C. F. S. Gomes, “Multicriteria decision-making in the selection of warships: a new approach to the AHP method,” International Journal of the Analytic Hierarchy Process, vol. 13, no. 1, pp. 147–169, 2021.

[11]       Z. Sener, “Evaluating ship selection criteria for maritime transportation,” Journal of Advanced Management Science, vol. 4, no. 4, 2016.

[12]       S.-L. Si, X.-Y. You, H.-C. Liu, and P. Zhang, “DEMATEL technique: A systematic review of the state-of-the-art literature on methodologies and applications,” Mathematical Problems in Engineering, vol. 2018, 2018.

[13]       A. Aghelie, N. M. Mustapha, S. Sorooshian, and N. A. Azizan, “Mathematical modeling of interrelationship analysis to determine multi-criteria decision making casual relations,” Journal of Advanced Research Design, vol. 20, no. 1, pp. 18–33, 2016.

[14]       Z. Sener and E. Ozturk, “A QFD-based decision model for ship selection in maritime transportation,” International Journal of Innovation, Management and Technology, vol. 6, no. 3, p. 202, 2015.

[15]       S. Abu-Assab, “Integration of preference analysis methods into QFD for elderly people,” in Integration of preference analysis methods into quality function deployment, Springer, 2012, pp. 69–86.

[16]       R. Wolniak, “The use of QFD method advantages and limitation,” Production Engineering Archives, vol. 18, 2018.

[17]       Z. L. Yang, S. Bonsall, and J. Wang, “Approximate TOPSIS for vessel selection under uncertain environment,” Expert Systems with Applications, vol. 38, no. 12, pp. 14523–14534, 2011.

[18]       A. Taroun and J.-B. Yang, “Dempster-Shafer theory of evidence: potential usage for decision making and risk analysis in construction project management,” 2011.

[19]       M. Liu, Y. Wu, W. Zhao, Q. Zhang, M. Li, and G. Liao, “Dempster–Shafer fusion of multiple sparse representation and statistical property for SAR target configuration recognition,” IEEE Geoscience and Remote Sensing Letters, vol. 11, no. 6, pp. 1106–1110, 2013.

[20]       M. CEDOLIN and Z. SENER, “An integrated fuzzy decision approach for selecting ships in maritime logistics,” in LM-SCM 2016 XIV. INTERNATIONAL LOGISTICS AND SUPPLY CHAIN CONGRESS, 2016, p. 587.

[21]       X. Ma, C. Ma, Z. Wan, and K. Wang, “A fuzzy chance-constrained programming model with type 1 and type 2 fuzzy sets for solid waste management under uncertainty,” Engineering Optimization, vol. 49, no. 6, pp. 1040–1056, 2017.

[22]       X. Xie, D.-L. Xu, J.-B. Yang, J. Wang, J. Ren, and S. Yu, “Ship selection using a multiple-criteria synthesis approach,” Journal of Marine Science and Technology, vol. 13, no. 1, pp. 50–62, 2008.

[23]       S. Wibowo and H. Deng, “Intelligent decision support for effectively evaluating and selecting ships under uncertainty in marine transportation,” Expert Systems with Applications, vol. 39, no. 8, pp. 6911–6920, 2012.

[24]       M. Velasquez and P. T. Hester, “An analysis of multi-criteria decision making methods,” International journal of operations research, vol. 10, no. 2, pp. 56–66, 2013.

[25]       C. Kahraman, M. Keshavarz Ghorabaee, E. K. Zavadskas, S. Cevik Onar, M. Yazdani, and B. Oztaysi, “Intuitionistic fuzzy EDAS method: an application to solid waste disposal site selection,” Journal of Environmental Engineering and Landscape Management, vol. 25, no. 1, pp. 1–12, 2017.

[26]       D. Stanujkic, E. K. Zavadskas, M. K. Ghorabaee, and Z. Turskis, “An extension of the EDAS method based on the use of interval grey numbers,” Studies in Informatics and Control, vol. 26, no. 1, pp. 5–12, 2017.

[27]       A. R. Mishra, A. Mardani, P. Rani, and E. K. Zavadskas, “A novel EDAS approach on intuitionistic fuzzy set for assessment of health-care waste disposal technology using new parametric divergence measures,” Journal of Cleaner Production, vol. 272, p. 122807, 2020.

[28]       X. Peng and C. Liu, “Algorithms for neutrosophic soft decision making based on EDAS, new similarity measure and level soft set,” Journal of Intelligent & Fuzzy Systems, vol. 32, no. 1, pp. 955–968, 2017.

Cite this Article as :
Abedallah Z. Abualkishik , Rasha Almajed , William Thompson, An Innovative Multi-Criteria Decision-Making (MCDM) Framework for Picking the Right Used Chemical Tankers: A Classified Model-Based Discussion, American Journal of Business and Operations Research, Vol. 7 , No. 2 , (2022) : 08-18 (Doi   :  https://doi.org/10.54216/AJBOR.070201)