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Optimization of combined ship routing and inventory management in the salmon farming industry
Norwegian University of Science and Technology, Faculty of Social Sciences and Technology Management, Department of Industrial Economics and Technology Management.
Norwegian University of Science and Technology, Faculty of Social Sciences and Technology Management, Department of Industrial Economics and Technology Management.
2014 (English)MasteroppgaveStudent thesis
Abstract [en]

Fish feed is the largest component of a salmon farmer’s production costs and lost feed days are a large cost driver. Norway’s largest salmon farmer, Marine Harvest Norway, hopes to cut costs and increase reliability of feed deliveries by starting in-house feed production and distribution. In order to deliver feed to fish farms from the new factory in an efficient and reliable way, they need to create cost-effective and robust transportation plans. The basis for this thesis is the problem of planning feed deliveries faced by Marine Harvest Norway, hereby referred to as Marine Harvest. The goal is to provide a model to simultaneously aid in routing of feed deliveries and inventory management. We have further developed our Inventory Routing Problem (IRP) model from Ivarsøy and Solhaug (2013) into three mathematical formulations. We have also developed two frameworks for parallel branch-and-bound, in an attempt to search through a larger part of the solution space in shorter time. The three formulations have been tested on three various-sized test cases, which differ in the number of fish farms considered, as well as production and transportation capacity. The largest test case is a realistic representation of the planning problem. Most of the parameters used are real data provided by Marine Harvest, while we have made our own estimations when needed. The first formulation is an arc-load formulation, similar to the one given in Ivarsøy and Solhaug (2013). The arc-flow and multi-commodity formulations are extensions of this, and include more detailed information about loads on board ships. Results showed that the arc-flow model performed best for all test cases. The arc-load model performed well for the smallest test case, while the multi-commodity model suffers from long solution times for each branch-and-bound-node and has scaling issues due to a large number of variables. The parallel frameworks did not work as well as hoped. The first framework parallelize the work of solving each branch-and-bound node, and did not manage to find any integer solutions or good lower bounds. The second framework is more promising, but our simple synchronous implementation only finds a marginally better solution than the sequential run, and the solution time was not decreased in accordance with the increased use of computing resources.

Place, publisher, year, edition, pages
Institutt for industriell økonomi og teknologiledelse , 2014. , 182 p.
URN: urn:nbn:no:ntnu:diva-26467Local ID: ntnudaim:11475OAI: diva2:747968
Available from: 2014-09-17 Created: 2014-09-17 Last updated: 2014-09-17Bibliographically approved

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