A matheuristic approach for the liner ship scheduling and container routing problem with transit time sensitive demand

Along with globalization, due to the gradual growth in commercial cargo volumes in maritime transportation, the use of operations research based decision support systems has gained great importance. Employment of proper transportation models incorporating cost and service quality considerations ensures that the right decisions are made at operational, tactical, and strategic levels. In this context, for an available transportation fleet, tactical planning of ship schedules and the routing of containers depending on the operational needs constitute the main problems to be solved in maritime transportation. Simultaneous handling of these problems is of great importance for obtaining high quality solutions based on the revenue, operational costs, and service quality measures. Similarly, transit times of the schedule and customer demand pattern are also important issues, which should be considered within the solution process. The problem under consideration is described as the integrated Liner Ship Scheduling and Container Routing Problem (LSSCRP). Since the problem is of NP-hard complexity, its optimal solution in a reasonable time is not possible in general. In this thesis, a matheuristic solution approach for the integrated problem LSSCRP is developed, where the effect of the transit times on customer demand is taken into consideration. For this purpose, the liner ship scheduling and the container routing with transit time sensitive demand are solved iteratively in a matheuristic framework employing a variable neighborhood search (VNS) algorithm. The performance of the developed LSSCRP matheuristic is tested on a set of different problems.