Another problem space that defines fleet management in its own way is Maritime support. This is not restricted to sea borne transportation and includes water-borne transportation as well. Ships and ports, their logistics and containers management and interconnections among vessels characterize this field.

There are three modes of transportation in maritime – liner, industrial and tramp. Adjustments to fleet size and mix, fleet deployment, ship routing and scheduling are some of the tactical problems. As with the airline transportation discussed earlier, the issue of robustness needs to be addressed here as well as disruptions are common. Therefore, robustness is factored into the optimization models used for planning.

Methodologies used towards solutions include input parameters, deterministic models that incorporate penalties and stochastic optimization models. One of the established techniques uses fleet composition and mix routing while another uses decision support methodology for strategic planning in tramp and industrial shipping. This involves simulation and optimization, where a Monte-Carlo simulation framework is built around an optimization-based decision support system and short term routing and scheduling using a rolling horizon principle where information is revealed as time goes by. This helps with a wide range of strategic planning problems.

When it comes to ferry scheduling, the analogy from public transit system discussed earlier hold true. The common objective is the minimization of costs and maximization of customer satisfaction. Decreasing the operational costs and reducing the travel time and waiting time for passengers requires reevaluation and improvements to the ferry schedule. There is a ‘logit’ model that determines’ the passengers’ service choices. This is used by the formulation to determine the best mixed-fleet operating strategy, including interlining schemes, so as to minimize the objective function that combines both the operator and passengers’ performance measures.