A MIP Based Local Search Heuristic for a Stochastic Maritime Inventory Routing Problem

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 of ships and multiple production and consumption ports with limited storage capacity. In spite of being one of the most common ways to transport goods, maritime transportation is characterized by high levels of uncertainty. The principal source of uncertainty is the weather conditions, since they have a great influence on sailing times. The travel time between any pair of ports is assumed to be random and to follow a log-logistic distribution. To deal with random sailing times we propose a two-stage stochastic programming problem with recourse. The routing, the order in which the ports are visited, as well as the quantities to load and unload are fixed before the uncertainty is revealed, while the time of the visit to ports and the inventory levels can be adjusted to the scenario. To solve the problem, a MIP based local search heuristic is developed. This new approach is compared with a decomposition algorithm in a computational study.