Heuristics for a Stochastic and Dynamic Routing Problem in Industrial Shipping

Vehicle routing problems are an essential element in transportation planning and logistics. In particular, maritime transportation plays a crucial role in international trade, managing most of long-distance shipments. Static and deterministic vehicle routing problems have been extensively studied in the literature and metaheuristics have shown to be capable of providing near optimal solutions for most of them. However, stochasticity is inherent in numerous important real applications, many of which are also dynamic, and this area is significantly more unexplored yet. In this direction, this paper approaches a dynamic and stochastic maritime transportation problem motivated by a real world application in industrial shipping. Three heuristics adapted to this problem are considered and their performance minimizing transportation costs is evaluated. Extensive computational testing to further highlight properties of the considered solution methods is provided and it shows that the use of stochastic information in the solution methods yields to an average cost saving of 2.5 % on a set of realistic test instances. Keywords— Maritime transportation, Scenario, Simulation, Tabu Search.