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 ch...
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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 algorithmconsiders a reduced formulation for the problem which performs much better than the complete one, and easily finds optimal solutions for the smaller and most of the clustered instances. The ALNS heuristiccontains 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. (c) 2021 Elsevier b.V. All rights reserved.
In this paper, we studied Virtual Private Network Design Problem using tree structure and assuming a pipe traffic matrix. Today with network virtualization, Virtual Private Networks (VPNs) have more importance in netw...
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ISBN:
(纸本)9781479951512
In this paper, we studied Virtual Private Network Design Problem using tree structure and assuming a pipe traffic matrix. Today with network virtualization, Virtual Private Networks (VPNs) have more importance in networking and offers the company the ideal solution to establish ondemand overlay networks that enable their customers to securely access company resources. This is a hard combinatorial optimization problem that it has been solved in literature only with approximation methods. Generally, this kind of methods do not give any guarantee on the solution quality and we are enable to know a priori how far the given solution is from the optimal one unlike other methods such as the exact methods. For this purpose, we propose an integer linear program (ILP) with classical Pipe traffic model to design the problem under investigation. based on the proposed integer programming formulation, we solve the problem using two approaches: The first contribution is Simulated Evolution based evolutionary algorithm and the second contribution is an exact method based on branch and cut (b&c) algorithm to find a tree rooted at a user specified node with minimized overall reserved bandwidth. Performance results using brite networks show that our proposed evolutionary algorithm offers good solutions within a fraction of the time required by the b&c algorithm and bandwidth cost within at most 1.5% of the optimal solutions found by the exact method.
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