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    Enhancing passage planning with fuzzy logic for sea navigation: A hybrid approach to cross track limit determination
    (Pergamon-Elsevier Science Ltd, 2025) Ayten, Abdulhamit; Fiskin, Remzi; Arslan, Omer; Galeazzi, Roberto
    Safe navigation in passage planning depends on multiple factors, including ship maneuverability, size, speed, traffic conditions, and Cross Track Limit (XTL). Traditionally, XTL settings are based on company policies, navigator experience, and subjective risk perception, which often leads to inconsistencies. To address this issue, this study introduces a structured decision-support framework that integrates the Fuzzy Extended Analytic Hierarchy Process (FE-AHP) with a Mamdani-type Fuzzy Inference System (FIS). FE-AHP was applied to systematically identify and rank factors affecting XTL, while the FIS generated context-sensitive recommendations. The analysis differentiates between open seas and confined waters. In open seas, static ship-related factors such as maneuverability (MOS), length (LOS), and width (WOS) dominate, whereas in confined waters, dynamic and environmental variables, including draft (DOS) and the Category Zone of Confidence (CATZOC), play a more decisive role. Numerical experiments demonstrated practical applicability. In open seas, XTL values ranged from 1.46 Nm in unfavorable conditions to 4.54 Nm under optimal ones, depending on ship features, navigator experience, and traffic risk. In confined waters, values were narrower, between 0.12 Nm (high draft, low CATZOC, inexperienced navigator) and 0.85 Nm in favorable settings. These results highlight that while open seas allow wider maneuvering margins, confined waters critically constrain navigation due to environmental and operational factors. By combining expert knowledge with quantitative modeling, the FE-AHP + FIS framework reduces reliance on subjective judgment and improves consistency in XTL determination. This structured approach supports more informed, data-driven passage planning and contributes to safer, more efficient maritime navigation.
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    Understanding the impact of ballast water management deficiencies on ship detentions: A hybrid predictive approach
    (Elsevier Sci Ltd, 2026) Arslan, Omer; Fiskin, Remzi
    Effective monitoring of ship compliance with international maritime regulations is vital for ensuring maritime safety and environmental protection. This study introduces a hybrid predictive framework aimed at assessing the likelihood of ship detentions based on Port State Control (PSC) inspection outcomes. The framework integrates four complementary methods: Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance, Random Forest (RF) to identify key predictors, Association Rule Mining (ARM) to uncover underlying patterns, and Logistic Regression (LR) to estimate marginal effects and interpret results. Using inspection data from oil/ chemical tankers under the Paris Memorandum of Understanding (MoU) between April 2021 and April 2024, the study places particular emphasis on detentions associated with deficiencies related to the Ballast Water Management (BWM) Convention. Key variables include ship size, inspection region, deficiency types and numbers, and the safety performance of operating companies. The results reveal that detention risk is significantly influenced by ship characteristics, regional inspection patterns, and both the type and numbers of deficiencies. Notably, BWM-related documentation issues (e.g., management plans, record books), low company performance, and inadequate crew training are strong predictors of detention. Methodologically, the RF model achieved a high predictive accuracy of 84.7 %, while ARM identified association rules with confidence levels up to 98 %, particularly for ships subject to expanded inspections with more than seven deficiencies. LR further confirmed the statistical significance of poor company performance and critical defect types through high odds ratios. Overall, the proposed framework offers a comprehensive, data-driven tool to support PSC authorities in identifying high-risk ships, enabling more efficient and targeted inspections while enhancing regulatory enforcement.