Abstract
To address the high environmental risk related to the increased oil tanker traffic in the High North, the Norwegian Coastal Administration (NCA) manages one of its vessel traffic service (VTS) centers in the town of Vardo, Norway. The fleet of tugboats, controlled by the VTS center operators, patrols the coastline to hook-up with any potential drifting oil tanker in the region of interest, before it runs ashore. Presently, the tugboats are controlled manually, which is not only challenging but less effective. In this paper, we develop two alternative binary integer programming models that give better tugboat policies in less computational time compared to previous work. Promising results with historical data illustrate great potential for optimal environmental risk reduction along the northern coast of Norway
Highlights
Maritime transportation plays an essential role in the international trade as it provides a cost-effective means to transport large cargo volumes
We present the risk model Riskωv for any vessel scenario ωv that helps to derive the risk for all scenarios ω, which represents the main function to be minimized in the two binary integer programming (BIP) models presented in Subsection 2.2
We address the environmental risk related to oil tankers traffic along the northern Norwegian coast
Summary
Maritime transportation plays an essential role in the international trade as it provides a cost-effective means to transport large cargo volumes. Previous works [5]-[9] consider a one-dimension modeling approach and focus on the minimization of the distances between potentially drifting vessels and the nearest tugboat by means of genetic algorithms and a mixed integer programming (MIP). Their model and algorithms allocate tugboats to oil tankers, but do not give information on the probability of successful hook-up. [11] develops a two-dimension mathematical model, with hook-up probabilities, that minimizes the expected cost of grounding accidents Despite these improvements, they do not account for uncertainty on weather conditions and use only one drift trajectory to predict the path followed by the potential drifting vessel.
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