Goal-based optimization in Arctic offshore support vessel design and fleet composition

The goal-based design (GBD) approach is a promising tool, supporting innovative solutions in conceptual ship and fleet design. Unlike traditional ship design methods, GBD aims to quantify different ship performance indicators to avoid prescripted rules and excessive reliance on prototypes, significantly extending the design space. Although the GBD approach is adapted to solve many ship and fleet design problems, its application for Arctic offshore support vessel design and fleet composition is still limited. Consequently, the thesis aims to advance the existing methods for goal-based optimization of Arctic offshore support vessels and fleets. The proposed approaches and framework consider issues related to the exploration and extraction stages of the development of Arctic offshore oil and gas fields. The existing methods for optimizing Arctic offshore exploration drilling support fleets rely on external expertise, resulting in limited design space and significant subjectivity of optimization constraints formulation. The performance of the Arctic offshore support fleet for the exploration stage of oil and gas field development is mainly related to specialized Arctic offshore supply vessels. The holistic ship design optimization approach represents an advanced GBD tool to find effective solutions in the conceptual ship design of complex vessels with a challenging operational context, like Arctic offshore supply vessels. However, it is believed that there is no holistic ship design optimization approach for ice-going vessels. Consequently, an integrated framework, including methods to address these existing gaps in the studied research field, is developed in this thesis. An Artificial Bee Colony-based approach to optimize Arctic offshore drilling support fleets for cost-efficiency is proposed. The approach provides a quantitative assessment of the versatile functionality of the fleet, considering the combined effect of the expected costs of accidental events, the versatility of individual support vessels, and the management of sea ice. As a result, the proposed method extends the design space and reduces subjectivity in Arctic offshore drilling support fleet optimization. Furthermore, this thesis proposes an approach for holistic multi-objective optimization of Arctic offshore supply vessels with in-depth consideration of their operational context. The framework scans the feasible design space to find a Pareto front, representing the tradeoffs between the cost- and eco-efficiency for a conceptual design of an Arctic offshore supply vessel. The provided case studies and verifications illustrate the validity and reliability of the developed approaches.