Implementation of the operational guidance as a part of the second generation intact stability criteria to the deterministic ship weather routing

The paper presents an innovative approach to ship route planning, with a Decision Support System (DSS) at its core. DSS integrates deterministic algorithms with safety constraints based on the Second Generation Intact Stability Criteria (SGISC), particularly the Operational Guidance (OG) implementin...

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Veröffentlicht in:Ocean engineering Jg. 333; S. 121455
Hauptverfasser: Zyczkowski, Marcin, Krata, Przemyslaw, Szozda, Zbigniew
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 30.07.2025
Schlagworte:
Decision support system prototyping
Decision-making for ship navigation
Deterministic algorithm
Machine learning
Operational guidance
Proactive ship stability assessment
Second generation intact stability criteria
Weather routing
Decision-making for ship navigation
Weather routing
Machine learning
Proactive ship stability assessment
Second generation intact stability criteria
Operational guidance
Deterministic algorithm
Decision support system prototyping
ISSN:0029-8018
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Zusammenfassung:The paper presents an innovative approach to ship route planning, with a Decision Support System (DSS) at its core. DSS integrates deterministic algorithms with safety constraints based on the Second Generation Intact Stability Criteria (SGISC), particularly the Operational Guidance (OG) implementing the SGSIC Level 2 assessment. A distinctive feature of the proposed method is the use of machine learning to create a surrogate model capable of supporting the identification of hazardous conditions and enhance adaptive decision-making. Combined with graph-based algorithms, this allows DSS to generate optimal routes that comply with the most modern stability standards. The system not only plans safe and efficient routes but also supports operational decisions by linking weather forecasts with the ship's dynamic stability. The methodology was tested using a computer model of the training vessel Horyzont II, covering failure modes such as surf-riding, parametric rolling, pure loss of stability, excessive acceleration, and synchronous rolling. The results demonstrate the system's effectiveness under various sea conditions and its potential to reduce accident risks. By integrating machine learning with route optimization and stability assessment, the proposed solution contributes to the development of intelligent navigation tools for both conventional and future autonomous vessels. •Ship weather routing combines deterministic algorithms with SGISC constraints.•DSS uses machine learning, and graph-based algorithms for route optimization.•Case study integrates a dynamic stability model for various failure modes.•Various routing scenarios confirm DSS reliability under diverse sea conditions.•Integrating stability constraints in routing enhances safety and decision-making.
ISSN:0029-8018
DOI:10.1016/j.oceaneng.2025.121455