Method for controlling the environmental risk in the maritime navigation sector

The redefined BAP with a Cuckoo Search Algorithm addresses computational complexity in berth allocation by integrating safety and environmental risk factors, optimizing port operations with a suboptimal yet effective solution.

WO2026126002A1 Publication Date: 2026-06-18MAIN SRL
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Patent Information

Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
MAIN SRL
Filing Date
2025-11-28
Publication Date
2026-06-18

AI Technical Summary

⚠Technical Problem

Existing berth allocation methods in maritime logistics primarily focus on economic optimization, neglecting safety and environmental risks associated with ship docking, which are computationally complex and often result in suboptimal solutions.

⚗Method used

A redefined Berth Allocation Problem (BAP) that incorporates a new cost function considering time, economic, and sustainability-risk factors, solved using a Cuckoo Search Algorithm (CSA) to balance these factors and minimize accidents and environmental impact.

🎯Benefits of technology

The method optimizes berth assignments by balancing economic and safety constraints, providing suboptimal yet effective solutions with manageable computational complexity, enhancing port operations' safety and efficiency.

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Abstract

The present invention provides some essential teachings for facing the problem of assigning berths to ships waiting to be serviced in a port in a way that also optimizes safety aspects. The method taught, therefore, involves setting up a BAP (Berth Allocation Problem) redefined to incorporate a completely new cost function, in which environmental and social risk costs are also taken into due account. Furthermore, the method taught, although incorporating a novel cost function, which significantly increases the complexity of the solution space, is configured to be addressed using a solution search algorithm, never previously used to solve a BAP in port applications, and executable with a largely acceptable computational complexity. In particular, the exploration of the solution tree, in search of an optimal or, more precisely, sub-optimal solution, is conducted through an adaptation of a Cuckoo Searc" type algorithm to this case.
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