Robust Optimization for a Maritime Inventory Routing Problem

Agostinho Agra (), Marielle Christiansen (), Lars Magnus Hvattum () and Filipe Rodrigues ()
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Agostinho Agra: Department of Mathematics and Center for Research and Development in Mathematics and Applications, University of Aveiro, 3810-193 Aveiro, Portugal
Marielle Christiansen: Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, 7491 Trondheim, Norway
Lars Magnus Hvattum: Molde University College, 6402 Molde, Norway
Filipe Rodrigues: Department of Mathematics and Center for Research and Development in Mathematics and Applications, University of Aveiro, 3810-193 Aveiro, Portugal

Transportation Science, 2018, vol. 52, issue 3, 509-525

Abstract: We consider a single product maritime inventory routing problem in which the production and consumption rates are constant over the planning horizon. The problem involves a heterogeneous fleet and multiple production and consumption ports with limited storage capacity. Maritime transportation is characterized by high levels of uncertainty, and sailing times can be severely influenced by varying and unpredictable weather conditions. To deal with the uncertainty, this paper investigates the use of adaptable robust optimization where the sailing times are assumed to belong to the well-known budget polytope uncertainty set. In the recourse model, the routing, the order of port visits, and the quantities to load and unload are fixed before the uncertainty is revealed, while the visit time to ports and the stock levels can be adjusted to the scenario. We propose a decomposition algorithm that iterates between a master problem that considers a subset of scenarios and an adversarial separation problem that searches for scenarios that make the solution from the master problem infeasible. Several improvement strategies are proposed aiming at reducing the running time of the master problem and reducing the number of iterations of the decomposition algorithm. An iterated local search heuristic is also introduced to improve the decomposition algorithm. A computational study is reported based on a set of real instances.

Keywords: robust optimization; uncertainty; travel time; decomposition; matheuristic; inventory routing (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (19)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:52:y:2018:i:3:p:509-525

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