Exact and heuristic algorithms for the fleet composition and periodic routing problem of offshore supply vessels with berth allocation decisions

Abstract This paper presents a branch-and-cut algorithm and an adaptive large neighborhood search (ALNS) heuristic for the periodic supply vessel planning problem (PSVPP) arising in the upstream offshore petroleum logistics chain. Platform supply vessels support the offshore oil and gas exploration and production activities by transporting all the necessary material and equipment back and forth between offshore units and an onshore supply base according to a delivery schedule. The PSVPP consists of solving a periodic vehicle routing problem and simultaneously determining an optimal fleet size and mix of heterogeneous offshore supply vessels, their weekly routes and schedules for servicing the offshore oil and gas installations, and the berth allocations at the supply base. The branch-and-cut algorithm considers a reduced formulation for the problem which performs much better than the complete formulation, and easily finds optimal solutions for the smaller and most of the clustered instances. The ALNS heuristic contains new features which include multiple starts and spaced local searches. These algorithms were tested on instances with up to 79 offshore units, providing better results than the best available.