Strategic Selection of Dredging Vessels for Port Maintenance

A multi-attribute trade-off analysis of stakeholders objectives

Master Thesis (2026)
Author(s)

T.A. Setiyanto (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

Alex Kirichek – Graduation committee member (TU Delft - Rivers, Ports, Waterways and Dredging Engineering)

José A. Á. Antolínez – Graduation committee member (TU Delft - Coastal Engineering)

A. Sepehri – Mentor

Sterre Neumann – Mentor (Port of Rotterdam)

Faculty
Civil Engineering & Geosciences
More Info
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Publication Year
2026
Language
English
Graduation Date
29-01-2026
Awarding Institution
Delft University of Technology
Programme
['Civil Engineering']
Faculty
Civil Engineering & Geosciences
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Abstract

Maintenance dredging keeps ports and waterways navigable by removing accumulated sediment that reduces water depth over time. Regular maintenance operations preserve the Nautical Guaranteed Depth and accommodate increasingly deep-draft vessels. Ports use different dredging methods depending on site conditions: Trailing Suction Hopper Dredgers (TSHD) and Grab Dredger (GD) removes sediment for disposal, while Water Injection Dredger (WID) and Bed Levellers (BL) redistributes material within the port system.

Current vessel selection practice relies heavily on experience and standard contract arrangements but rarely evaluates trade-offs between production efficiency, operational cost, and emissions systematically. High-production vessels often incur higher costs and emissions, while cost-efficient vessels may operate too slowly for time-sensitive projects. Low-emission vessels tend to have limited throughput, creating difficult compromises when navigational access must be maintained within budget and environmental constraints. Existing decision frameworks rarely integrate these technical constraints with stakeholder preferences in a transparent and reproducible way, so planners may lack structured guidance when operational conditions deviate from routine cases or when policy priorities shift.

This study develops a simulation-based ranking framework that quantifies vessel performance across production, cost, and emissions, then ranks alternatives using multi-attribute decision-making methods. The framework implements vessel-specific production models and cycle-time accounting across operational phases. Energy consumption during sailing phases is calculated using OpenTNSim's resistance-based approach, while dredging phases use load fraction models based on installed power and contractor-provided operating ranges. Emissions are calculated from phase-specific energy consumption using fuel-specific emissions factors for each vessel. Stakeholder preferences are elicited using the Best-Worst Method (BWM) from representatives of the Port Authority, Dredging Contractor, and Rijkswaterstaat, with stakeholder influence quantified through Power-Interest analysis and Structured Expert Judgement (SEJ) calibration. Vessel rankings are generated using VIKOR, which identifies compromise solutions by balancing overall performance with the weakest criterion for each vessel, and PROMETHEE II evaluates vessels through systematic pairwise comparisons and aggregates these into net preference flows, which reflect how strongly each vessel outperforms others and how strongly it is outperformed in return. Applying both methods enables an assessment of methodological robustness through subsequent rank correlation analysis.

Six scenarios were evaluated, representing different basin locations, sediment contamination levels, and operational constraints in Perceel 4. Composite objective weights derived from stakeholder elicitation are 49.8% for production, 43.0% for cost, and 7.2% for emissions, reflecting current operational priorities where maintaining navigational access and staying within budget dominate over environmental concerns. VIKOR and PROMETHEE II show high agreement, producing almost identical rankings (Spearman ρ = 0.9333, Kendall τ = 0.9667). WID achieves the best average rank in scenarios due to balanced performance on production, cost, and emissions. TSHD-B delivers the highest production but gets excluded in half the scenarios because of draft and size limitations. The main finding is that operational constraints often override efficiency advantages: matching vessel capabilities to site-specific requirements usually determines suitability before performance metrics come into play. The framework shows which vessels perform well under which conditions, why rankings shift when priorities change, and where feasibility boundaries lie.

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