A flexible decision-support solution for intervention measures of grounded ships in the Yangtze River. (1st September 2017)

• Record Type: Journal Article
• Authors: Wu, Bing; Yan, Xinping; Yip, Tsz Leung; Wang, Yang
• Is Part Of: Ocean engineering. Volume 141(2017)
• Page Start: 237
• Page End: 248
• Publication Date: 2017-09-01
• Subjects: Grounding accidents -- Flexible decision support -- Bayesian network -- Intervention measures; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2017.06.021
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: Groundings are frequently occurring accidents that pose a serious risk in inland waterways. This paper proposes a flexible decision-support solution for grounded ships in the Yangtze River. The basis of the proposed method is to develop an influence diagram based on a three-layer decision-making framework, to consider the effectiveness of the intervention measures by adding two nodes and establishing the associated conditional probability tables, and to merge the influence diagram and the intervention measures as a flexible decision-support solution. The merits of the proposed method include the intuitive representation of how the influencing factors affect the alternatives using a graphical structure, the flexibility to implement and to consider the intervention measures for grounded ships, and the ability to deal with uncertainty in both numerical data and qualitative information. The results of the case study showed that it is unanimous with the real situations and the intervention measures should be considered to make effective and accurate decision-making for grounding ships. Consequently, the method presented in this paper provides a practical and flexible decision-support solution for grounded ships. Highlights: Influence diagram based decision support solution is developed for grounded ships. Proposed solution is flexible to consider the intervention measures for grounded ships. Proposed solution can deal with both numerical and qualitative uncertainties.