| dc.description.abstract | This thesis considers operational planning and disruption management in the offshore supply service in Statoil, the biggest Norwegian oil and gas company. A significant amount of time is needed for operational planning, and major costs are caused by disruptions to the planned routes and schedules for the offshore supply vessels (OSVs) supplying the offshore installations. The disruptions are mainly due to uncertain and harsh weather conditions, unexpected orders placed by offshore installations, and uncertain order volumes. A decision tool based on mathematical models may contribute to reducing the costs and time related to planning and disruption management in the offshore supply service.
Mathematical models handling disruptions and finding new routes and schedules for OSVs are presented. The problem is modelled as a pickup and delivery problem with time limits. Exact solution methods are introduced, and due to the complexity of the problem, a heuristic is developed to solve realistic instances that the exact models are not able to solve within a reasonable amount of time.
The problem instances are based on data provided by Statoil. The computational study compares the solutions of the proposed models. The results from the computational study show that the heuristic finds optimal solutions for all the problem instances where optimality can be proven by the exact methods, and has a stable performance for the other larger instances. The heuristic can form the basis for a decision support tool that can be utilized in everyday operational planning and disruption management by Statoil. Applying the heuristic for decision support can reduce the time spent on planning, and significant cost reductions can be made in the offshore supply service. | |
