Abstract. This paper considers a vessel pickup and delivery problem that arises in the case of disruptions in the supply vessel logistics in the offshore oil and gas industry. The problem can be modelled as a multivehicle pickup and delivery problem where delivery orders are transported by supply vessels from an onshore supply base (depot) to a set of offshore oil and gas installations, while pickup orders are to be transported from the installations back to the supply base (i.e. backload). We present both an arc-flow and a path-flow formulation for the problem. For the path-flow formulation we also propose an efficient dynamic programming algorithm for generating the paths, which represent feasible vessel voyages. It is shown through a computational study on various realistic test instances provided by a major oil and gas company that the path-flow model is superior with respect to computational performance.
This paper studies operational planning and disruption management in offshore oil and gas logistics.A significant amount of time is currently spent on operational planning, and major costs are caused by disruptions to the planned routes and schedules for the offshore supply vessels supplying the offshore installations. The disruptions are mainly due to uncertain and harsh weather conditions.To be able to solve real size instances of the planning problem, a variable neighborhood search heuristic is proposed, and tested on instances based on data provided by the case company. The computational results show that the heuristic finds optimal solutions for all the problem instances where the optimal solution is known, and finds high quality solution for larger instances.
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