Context & Challenge

Situated at the mouth of the Sognefjord, Gulen municipality is characterized by a demanding coastal topography. The region relies heavily on its local and county road infrastructure for daily commuting and commercial logistics. However, the rugged terrain restricts much of this network to single-lane roads. Consequently, traffic flow is frequently disrupted by sudden braking and the need for vehicles to reverse to accommodate oncoming traffic.

Thesis Objectives

The core task is to improve regional transit efficiency through a two-phase approach:

1. Diagnostic Analysis: Conduct a detailed evaluation of current travel times between key hubs in Gulen to identify and quantify the primary factors causing delays.
2. Analytical Modeling: Using these findings, develop an analytical model to help decision-makers strategically target and prioritize road infrastructure improvements.

Supervisor: Julio C. Góez.

The aim of the project is to  analyze current scheduling practices, identify inefficiencies caused by treating forecasts as firm orders, and propose improved methods for inventory placement and demand management.

Supervisor: Sigrid Lise Nonås.

The aim of the project is to investigate the impact of weather conditions on port operational efficiency, and provide predictions of port calling time.

Supervisor: Gabriel Fuentes.

This project aims to explore the application of AI models to enhance the tracking, prediction and reporting of emissions in maritime transportation in an increasingly regulated environment. By integrating advanced machine learning and generative AI techniques, the project aims at understand the potential and chanllenges.

Supervisor: Gabriel Fuentes.

This project will leverage data analytics models to predict spot freight rates and assess the value of foresight in key drivers such as supply and demand dynamics, vessel spatial positioning, and other critical factors. The research aims to empirically investigate the theoretically implied market efficiency, providing insights into how predictive accuracy can enhance decision-making and optimize market outcomes.

Supervisor: Gabriel Fuentes.

This project aims to investigate the implications, efficiency, and effectiveness of the EU’s FuelEU Maritime regulation on bunker fuel consumption, with a focus on its impact on ship operations and trade. The research will explore the various compliance strategies available to ship operators and owners as the regulation comes into force in January 2025.

The project will assess the flexibility and economic viability of different decision-making pathways, helping stakeholders determine the most cost-effective and strategic choices for maintaining compliance under the evolving regulatory framework.

Supervisor: Gabriel Fuentes.

This project aims to identify key trading signals and develop trading strategies for the ship spot and short-term chartering markets. By leveraging analytics and predictive modeling techniques, the goal is to uncover actionable insights that can optimize decision-making in spot market trades and short-period charters.

Supervisor: Gabriel Fuentes.

How to build future sustainable offshore logistics. Shipping technology, fleet renewal, energy-efficient operations will become crucial in the path towards zero-emission logistics along the Norwegian continental shelf. This topics is part of a large project in collaboration with main Norwegian stakeholders.

Supervisor: Mario Guajardo.

This project studies several topics on optimization models and methods for decision support in production of dairy and meat products. The aim is to improve profitability while reducing greenhouse gas emissions of the farming sector in Norway. It is part of a large project in collaboration with the main Norwegian stakeholders in this sector.

Supervisor: Mario Guajardo.

Utilizing weather data and AIS data, we aim to evaluate the influence of climatic events on routine maritime trade operations. Significant events, such as the draught restriction in the Panama Canal due to severe droughts, have resulted in costlier transits and prolonged waiting time durations. This thesis can investigate the externality cost of severe weather patterns, such as intensified El Niño.

Supervisor: Gabriel Fuentes

By quantifying shipping emissions, including greenhouse gases (GHGs) and sulfur, a thesis on this topic can investigate the impact of maritime climate-related policies on the overall trajectory of vessel emissions. There's ongoing debate surrounding regulations like the IMO 2020 Sulphur Cap and the introduction of measures like the Carbon Intensity Indicator (CII). We will evaluate the appropriateness and effectiveness of these regulations.

Supervisor: Gabriel Fuentes

Maritime investments face uncertainties with evolving climate-related policies. A seemingly recent and valuable asset today might become obsolete or uncompetitive due to policy shifts in the near future. A thesis on this topic could aim to introduce a model that navigates potential scenarios related to the progression of climate policies.

Supervisor: Gabriel Fuentes

In the oil and gas industry, helicopters are widely used for personnel and cargo transport between offshore platforms and heliports on the land. Therefore, the decision-making regarding the composition of the helicopter fleet and the allocation of this resource is vital for a stable operation of oil & gas exploration and extraction. Such tactical decision affects various aspects of an oil company, including contract utilization, carbon footprint, plan robustness and operating expenses.

However, the common practice in the industry is that the decision of fleet composition and allocation is still manually made based on demand forecast and individual’s experience. Such decision-making process cannot guarantee optimal solutions, is not scalable, and would likely lead to low resource utilization rate and high operating cost.

We are now seeing a clear trend in the oil and gas industry which is to apply automation in its various and complex decision-making process with the support of optimization. In terms of the helicopter fleet composition and allocation problem in this case, a decision support tool is expected to facilitate the decision of helicopter chattering and deployment with stochastic demand for the next planning period. Moreover, resource sharing, namely utilizing idle helicopter resources from other operators, is also a promising opportunity to increase the overall efficiency on an industry level and hence is becoming increasingly popular among different oil companies and helicopter operators.

With its trademark solution DaWinci as the industry standard in personnel logistics management, Quorum is the software supplier for many of the largest oil and gas companies in the world. Quorum Software Norway, as the market leader, is now cooperating with several major players in the oil and gas industry to address various new challenges with new software planning tools. This master project will take advantage of Quorum’s expertise in logistics management in oil and gas industry, and look at some of the following issues:

• Literature review on related problems and topics
• Mathematical formulation of the problem
• Study the uncertainty involved in this problem and methods to handle such stochasticity
• Study and develop necessary solution methods
• Analyze the numerical results based on a realistic problem instance from Quorum

Students choosing this project should expect to visit Quorum Software’s Bergen office to work alongside our optimization engineers for up to a week.

Collaborator: Quorum Software, contact person Xin Wang (xin.e.wang@quorumsoftware.com).

Supervisor: Yewen Gu.

Using empirical case studies to quantify how more accurate short-term weather forecasting can improve chartering decisions for a ship operator.

Supervisor: Gabriel Fuentes.

For e.g. breakbulk and chemical shipping companies it is challenging to find out which cargoes fit best together into a voyage such that all cargoes can be transported on voyages and ships travel the least possible distance. The aim of this topic is to create a model with typical restrictions and find a good weighing of the different aspects of the objective function. In cooperation with Dataloy Systems, you can use data to develop and test your model as well as discuss the underlying concepts.

Supervisor: Julio Cesar Goez

Urban population growth is driving an increase in the amount of freight that goes into and out of cities. That growth poses an increasing challenge to freight transportation in smaller compact cities with difficult topology, which is typical for most Norwegian cities and numerous cities abroad.

This transportation challenge is exacerbated by phenomena such as an increase in internet trade, the demand for fast delivery, and a reduction in the ownership of private cars in the city centre which could be used for shopping. The result is an increase in the total volume of freight, and more critically, in the total number of deliveries, normally managed by a large variety of transportation companies.

Unless planned for and regulated, a consequence might be increased traffic, with enhanced energy consumption, that competes for available space and may affect living conditions for a growing urban population.

This project will study small city logistics, with a focus on Bergen, to find the options available for the authorities, business models for a better city logistics setup, as well as mathematical modeling. Will be done in cooperation with the City of Bergen, Vestland County, Bergen Chamber of Commerce and Centre for Climate and Energy Transformation (CET) at The University of Bergen. The project can be qualitative as well as quantitative.

Possible supervisors: Stein W. Wallace or Julio C. Goez.

The aim of emergency medical services (EMS) is to provide timely assistance to emergencies in order to save lives. Within this service, quality and capacity have sometimes deteriorated because staffing is not satisfactory and because the organization and directives are not clear. My interest is to work on the use of autonomous vessels to help ameliorate the burden that EMS staffing represents in the case of boat ambulances, and to improve the logistics planning of the system.

The aim is to analyze the use of autonomous vessels to improve response times and coverage. For example, by combining autonomous vessels with geographic information systems, one may use real time information of potential patients to improve the deployment of the resources. In particular my interest is to explore the following key research topic: designing algorithms with predictive capabilities that can be included in real time systems and capable of managing a continuous feed of data points coming from users’ cell phones and other sources.

Supervisor: Julio C. Goez.

Car-sharing provides short-term vehicle access to a group of user members who share the use of a vehicle fleet owned by a car-sharing organization that maintains, manages, and insures the vehicles. An example of this model in Bergen is bildeleringer. Managing the fleet involves decisions such as the size of the fleet, how to position and reposition the vehicles, maintenance schedules, and pricing approaches. Strong background on analytics required

Supervisor: Julio C. Goez