An integrated optimization method for tactical-level planning in liner shipping with heterogeneous ship fleet and environmental considerations. (April 2021) - Pasha, Junayed; Dulebenets, Maxim A.; Fathollahi-Fard, Amir M.; Tian, Guangdong; Lau, Yui-yip; Singh, Prashant; Liang, Benbu
Highlights: An integrated optimization model is developed for liner shipping. The model captures all the major tactical-level planning decisions. The deployment of a heterogeneous ship fleet is allowed at each route. A decomposition-based heuristic is designed to solve the model. Numerical experiments demonstrate the efficiency of the heuristic. Managerial insights are illustrated using the developed model. Abstract: The maritime transportation flows and container demand have been increasing over time, although the COVID-19 pandemic may slow down this trend for some time. One of the common strategies adopted by shipping lines to efficiently serve the existing customers is the deployment of large ships. The current practice in the liner shipping industry is to deploy a combination of ships of different types with different carrying capacities (i.e., heterogeneous fleet), especially at the routes with a significant demand. However, heterogeneous fleets of ships have been investigated by a very few studies addressing the tactical liner shipping decisions (i.e., determination of service frequency, ship fleet deployment, optimization of ship sailing speed, and design of ship schedules). Moreover, limited research efforts have been carried out to simultaneously capture all the major tactical liner shipping decisions using a single solution methodology. Therefore, this study proposes an integrated optimization model that addresses all the major tactical liner shipping decisions and allows the deployment of a heterogeneous ship fleet at each route, considering emissions generated throughout liner shipping operations. The model's objective maximizes the total turnaround profit generated from liner shipping operations. A decomposition-based heuristic algorithm is presented in this study to solve the model proposed and efficiently tackle large-size problem instances. Numerical experiments, carried out for a number of real-world liner shipping routes, demonstrate the effectiveness of the proposed methodology. A set of managerial insights, obtained from the proposed methodology, are also provided.