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A Risk Assessment of Ships Groundings in Rivers: The Case of Parana River

Published online by Cambridge University Press:  11 December 2019

Hristos Karahalios
Hristos Karahalios*
Affiliation:
(Maritime Education Department, Pelorus, Athens, Nea Smyrni, Greece)
*
(E-mail: hristos_karahalios@hotmail.com)
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Abstract

A ship's grounding appears to be a significant threat to the safety of its crew, marine environment and the local ports economy. The risk of such incidents is higher in rivers since weather conditions can significantly alter the depths of channels from those shown on navigation charts. By means of a fuzzy analytic hierarchy process, a new methodology is proposed, capable of evaluating the hazards of a ship's grounding in a river. The proposed method contributes to safe navigation in rivers. Navigators are able to assess grounding risk in a river passage based on local information of past incidents. The proposed methodology is used to evaluate commercial risks from groundings in the Parana River. A case study was carried out using data from 118 cases, as provided by local agencies for the period 2008–2017.

Keywords

NavigationFuzzy Analytic Hierarchy ProcessCoastal Navigation
Type
Research Article
Information
The Journal of Navigation , Volume 73 , Issue 4 , July 2020 , pp. 833 - 845
Copyright
Copyright © The Royal Institute of Navigation 2019

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References

REFERENCES

Akyuz, E., Karahalios, H. and Celik, M. (2015). Assessment of the maritime labour convention compliance using balanced scorecard and analytic hierarchy process approach. Maritime Policy & Management, 42(2), 1–18.CrossRefGoogle Scholar
Asgari, N., Hassani, A., Jones, D. and Nguye, H. H. (2015). Sustainability ranking of the UK major ports: methodology and case study. Transportation Research Part E: Logistics and Transportation Review, 78, 19–39.10.1016/j.tre.2015.01.014CrossRefGoogle Scholar
Ayag, Z. and Özdemir, R. G. (2006). A fuzzy AHP approach to evaluating machine tool alternatives. Journal of Intelligent Manufacturing, 17(2), 179–190.CrossRefGoogle Scholar
Beikkhakhian, Y., Javanmardi, M., Karbasian, M. and Khayambashi, B. (2015). The application of ISM model in evaluating agile suppliers selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods. Expert Systems with Applications, 42(15), 6224–6236.10.1016/j.eswa.2015.02.035CrossRefGoogle Scholar
Buldgen, L., Bela, A. and Philippe, R. (2015). Simplified analytical methods to analyze lock gates submitted to ship collisions and earthquakes. Mathematical Modelling in Civil Engineering, 11(3), 8–22.CrossRefGoogle Scholar
Celik, M. (2009). Designing of integrated quality and safety management system (IQSMS) for shipping operations. Safety Science, 47(5), 569–577.10.1016/j.ssci.2008.07.002CrossRefGoogle Scholar
Cheng, A. C., Yang, B. K. and Hwang, C. (1999). Evaluating attack helicopters by the AHP based on linguistic variable weight. European Journal of Operational Research, 116, 423–435.10.1016/S0377-2217(98)00156-8CrossRefGoogle Scholar
Choi, J., Lee, D., Kang, H. J., Kim, S. Y. and Shin, S. C. (2014). Damage scenarios and an onboard support system for damaged ships. International Journal of Naval Architecture and Ocean Engineering, 6(2), 236–244.10.2478/IJNAOE-2013-0175CrossRefGoogle Scholar
Choung, J., Nam, J. M. and Tayyar, G. T. (2014). Residual ultimate strength of a very large crude carrier considering probabilistic damage extents. International Journal of Naval Architecture and Ocean Engineering, 6(1), 14–26.10.2478/IJNAOE-2013-0160CrossRefGoogle Scholar
Ebrahimnejad, S., Mousavi, S. M. and Seyrafianpour, H. (2010). Risk identification and assessment for build-operate-transfer projects: a fuzzy multi attribute decision making model. Expert Systems with Applications, 37, 575–586.10.1016/j.eswa.2009.05.037CrossRefGoogle Scholar
Erol, S. and Başar, E. (2015). The analysis of ship accident occurred in Turkish search and rescue area by using decision tree. Maritime Policy & Management, 42(4), 377–388.CrossRefGoogle Scholar
Fenstad, J., Dahl, Ø and Kongsvik, T. (2016). Shipboard safety: exploring organizational and regulatory factors. Maritime Policy & Management, 43(5), 552–568.CrossRefGoogle Scholar
Guo, S. and Zhao, H. (2015). Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective. Applied Energy, 158, 390–402.CrossRefGoogle Scholar
Havold, J. and Nesset, E. (2009). From safety culture to safety orientation: validation and simplification of a safety orientation scale using a sample of seafarers working for Norwegian ship owners. Safety Science, 47, 305–326.10.1016/j.ssci.2008.05.002CrossRefGoogle Scholar
Joshi, D. and Kumar, S. (2016). Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making. European Journal of Operational Research, 248(1), 183–191.10.1016/j.ejor.2015.06.047CrossRefGoogle Scholar
Kaplan, R. S. and Norton, D. P. (1996). Linking the balanced scorecard to strategy. California Management Review, 39(1), 53–79.CrossRefGoogle Scholar
Kaplan, R. S. and Norton, D. P. (2004). Measuring the strategic readiness of intangible assets. Harvard Business Review, 82(1), 52–63.Google ScholarPubMed
Kaplan, R. S. and Norton, D. P. (2005). The office of strategy management. Harvard Business Review, 83(10), 72–80.Google ScholarPubMed
Karahalios, H. (2017). The application of the AHP-TOPSIS for evaluating ballast water treatment systems by ship operators. Transportation Research Part D Transport and Environment, 52(Part A), 172–184.10.1016/j.trd.2017.03.001CrossRefGoogle Scholar
Karahalios, H., Yang, Z. L., Williams, V. and Wang, J. (2011). A proposed system of hierarchical scorecards to assess the implementation of maritime regulations. Safety Science, 49, 450–462.CrossRefGoogle Scholar
Kowalski, A. (2013). Traffic engineering methods solutions of problems concerning ship's manoeuvres and sailing on the large rivers of Central America. Scientific Journals Maritime University of Szczecin, 33(105), 57–61.Google Scholar
Kubler, S., Robert, J., Derigent, W., Voisin, A. and Le Traon, Y. (2016). A state-of-the-art survey & testbed of fuzzy AHP (FAHP) applications. Expert Systems Applications, 65, 398–422.CrossRefGoogle Scholar
Łozowicka, D. and Kaup, M. (2015). Analysis of the cause and effect of passenger ship accidents in the Baltic Sea. Scientific Journals of the Maritime University of Szczecin, 44(168), 68–73.Google Scholar
Mazaheri, A., Montewka, J. and Kujala, P. (2014). Modeling the risk of ship grounding—a literature review from a risk management perspective. WMU Journal of Maritime Affairs, 13(2), 269–297.CrossRefGoogle Scholar
Mondragon, M. and Escofet, A. (2013). Analysis of environmental bonds in Mexican pacific major ship grounding. Journal of Environmental Protection, 4(08), 65.10.4236/jep.2013.48A2008CrossRefGoogle Scholar
Morgan, A. D., Shaw-Brown, K., Bellingham, I., Lewis, A., Pearce, M. and Pendoley, K. (2014). Global Oil Spills and Oiled Wildlife Response Effort: Implications for Oil Spill Contingency Planning. International Oil Spill Conference Proceedings (Vol. 2014, No. 1). American Petroleum Institute, 1524–1544.CrossRefGoogle Scholar
Pak, J. Y., Yeo, G. T., Oh, S. W. and Yang, Z. (2015). Port safety evaluation from a captain's perspective: the Korean experience. Safety Science, 72, 172–181.CrossRefGoogle Scholar
Papanikolaou, A., Hamann, R., Lee, B. S., Mains, C., Olufsen, O., Vassalos, D. and Zaraphonitis, G. (2013). GOALDS—goal based damage ship stability and safety standards. Accident Analysis & Prevention, 60, 353–365.CrossRefGoogle ScholarPubMed
Park, K. S. and Lee, J. (2008). A new method for estimating human error probabilities: AHP-SLIM. Reliability Engineering and System Safety, 93, 578–587.CrossRefGoogle Scholar
Perepelkin, M., Knapp, S., Perepelkin, G. and Pooter, M. (2010). An improved methodology to measure flag performance for the shipping industry. Marine Policy, 34, 395–405.CrossRefGoogle Scholar
Punniyamoorthy, M. and Murali, R. (2008). Balanced score for the balanced scorecard: a benchmarking tool. Benchmarking: An International Journal, 15, 420–443.CrossRefGoogle Scholar
Ren, J. and Lützen, M. (2015). Fuzzy multi-criteria decision-making method for technology selection for emissions reduction from shipping under uncertainties. Transportation Research Part D: Transport and Environment, 40, 43–60.CrossRefGoogle Scholar
Saaty, T. L. (1994). How to make a decision: the analytic hierarchy process. Interfaces, 24(6), 19–43.CrossRefGoogle Scholar
Shafia, M. A., Mazdeh, M. M., Vahedi, M. and Pournader, M. (2011). Applying fuzzy balanced scorecard for evaluating the CRM performance. Industrial Management & Data Systems, 111(7), 1105–1135.CrossRefGoogle Scholar
Sun, B., Hu, Z. and Wang, G. (2015). An analytical method for predicting the ship side structure response in raked bow collisions. Marine Structures, 41, 288–311.CrossRefGoogle Scholar
Tavana, M. and Hatami-Marbini, A. (2011). A group AHP-TOPSIS framework for human spaceflight mission planning at NASA. Expert Systems Applications, 38(11), 13588–13603.Google Scholar
Tung, A., Baird, K. and Schoch, H. P. (2011). Factors influencing the effectiveness of performance measurement systems. International Journal of Operations & Production Management, 31(12), 1287–1310.10.1108/01443571111187457CrossRefGoogle Scholar
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.CrossRefGoogle Scholar
Uğurlu, Ö, Erol, S. and Başar, E. (2016). The analysis of life safety and economic loss in marine accidents occurring in the Turkish Straits. Maritime Policy & Management, 43(3), 356–370.10.1080/03088839.2014.1000992CrossRefGoogle Scholar
Ung, S. T., Williams, V., Chen, H. S., Bonsall, S. and Wang, J. (2006). Human error assessment and management in port operations using Fuzzy AHP. Marine Technology Society Journal, 40(1), 73–86.CrossRefGoogle Scholar
Vargas, L. G. (1982). Reciprocal matrices with random coefficients. Mathematical Modelling, 3(1), 69–81.CrossRefGoogle Scholar
Veisi, H., Liaghati, H. and Alipour, A. (2016). Developing an ethics-based approach to indicators of sustainable agriculture using analytic hierarchy process (AHP). Ecological Indicators, 60, 644–654.CrossRefGoogle Scholar
Vinodh, S., Shivraman, K. S. and Viswesh, S. (2012). AHP-based lean concept selection in a manufacturing organization. Journal of Manufacturing Technology Management, 23(1), 124–136.CrossRefGoogle Scholar
Wang, Y. M. and Parkan, C. (2006). Two new approaches for assessing the weights of fuzzy opinions in group decision analysis. Information Sciences, 176, 3538–3555.CrossRefGoogle Scholar
Wedley, W. C. (1993). Consistency prediction for incomplete AHP matrices. Mathematic Computer Modelling, 17(415), 151–161.10.1016/0895-7177(93)90183-YCrossRefGoogle Scholar
Wu, S. I. and Liu, S. Y. (2010). The performance measurement perspectives and cause relationship for ISO-certified companies: a case of opto-electronic industry. International Journal of Quality & Reliability Management, 27(1), 27–47.CrossRefGoogle Scholar
Young, C. N., Schopmeyer, S. A. and Lirman, D. (2012). A review of reef restoration and coral propagation using the threatened genus Acropora in the Caribbean and Western Atlantic. Bulletin of Marine Science, 88(4), 1075–1098.CrossRefGoogle Scholar
Yu, Z., Hu, Z., Amdahl, J. and Liu, Y. (2013). Investigation on structural performance predictions of double-bottom tankers during shoal grounding accidents. Marine Structures, 33, 188–213.CrossRefGoogle Scholar
Yu, Z., Hu, Z. and Wang, G. (2015). Plastic mechanism analysis of structural performances for stiffeners on bottom longitudinal web girders during a shoal grounding accident. Marine Structures, 40, 134–158.CrossRefGoogle Scholar
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.CrossRefGoogle Scholar
Zheng, G., Zhu, N., Tian, Z., Chen, Y. and Sun, B. (2012). Application of a trapezoidal fuzzy AHP method for work safety evaluation and early warning rating of hot and humid environments. Safety Science, 50(2), 228–239.10.1016/j.ssci.2011.08.042CrossRefGoogle Scholar