Short-term liner ship fleet planning with container transshipment and uncertain container shipment demand

• Published in: European journal of operational research Vol. 223; no. 1; pp. 96 - 105
• Main Authors: Meng, Qiang, Wang, Tingsong, Wang, Shuaian
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 16.11.2012; Elsevier; Elsevier Sequoia S.A
• Subjects: Algorithms; Applied sciences; Assignment problem; Container transshipment and uncertain demand; Containers; Demand; Exact sciences and technology; Expected values; Ground, air and sea transportation, marine construction; Integer programming; Liner shipping; Liners; Logistics; Marine and water way transportation and traffic; Marketing; Mathematical models; Mathematical programming; Motor vehicle fleets; Operational research and scientific management; Operational research. Management science; Route optimization; Sample average approximation with dual decomposition and Lagrangian relaxation; Shipments; Ships; Stochastic integer programming; Studies; Liner shipping; Container transshipment and uncertain demand; Sample average approximation with dual decomposition and Lagrangian relaxation; Stochastic integer programming; Logistics; Short term; Stochastic model; Subgradient optimization; Fleet; Decomposition method; Duality; Modeling; Stochastic programming; Integer programming; Container; Uncertain system; Transhipment; Transportation network; Profit; Ship; Planning; Maritime transportation
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2012.06.025

► We study a liner ship fleet deployment problem with container transshipment and uncertain container demand. ► This proposed problem is formulated as a two-stage stochastic programming model. ► An efficient global optimization algorithm is proposed. This paper proposes a short-term liner ship fleet planning problem by taking into account container transshipment and uncertain container shipment demand. Given a liner shipping service network comprising a number of ship routes, the problem is to determine the numbers and types of ships required in the fleet and assign each of these ships to a particular ship route to maximize the expected value of the total profit over a short-term planning horizon. These decisions have to be made prior to knowing the exact container shipment demand, which is affected by some unpredictable and uncontrollable factors. This paper thus formulates this realistic short-term planning problem as a two-stage stochastic integer programming model. A solution algorithm, integrating the sample average approximation with a dual decomposition and Lagrangian relaxation approach, is then proposed. Finally, a numerical example is used to evaluate the performance of the proposed model and solution algorithm.