Liner ship fleet deployment with week-dependent container shipment demand

• Published in: European journal of operational research Vol. 222; no. 2; pp. 241 - 252
• Main Authors: Meng, Qiang, Wang, Shuaian
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 16.10.2012; Elsevier; Elsevier Sequoia S.A
• Subjects: Applied sciences; Computer networks; Containerization; Containers; Demand; Exact sciences and technology; Ground, air and sea transportation, marine construction; Liner ship fleet deployment; Logistics; Marine and water way transportation and traffic; Marketing; Mathematical models; Mathematical programming; Operational research and scientific management; Operational research. Management science; Optimization algorithms; Routing; Routing (telecommunications); Shipments; Space–time network model; Studies; Transit time; Transit time constraint; Week-dependent container shipment demand; Week-dependent container shipment demand; Transit time constraint; Space–time network model; Liner ship fleet deployment; Logistics; Lower bound; Fleet; Transit time; Unfolding; Space-time network model; Global optimum; Routing; Modeling; Container; Transportation network; Occupation time; Planning; Maritime transportation
• ISSN: 0377-2217; 1872-6860; 1872-6860
• DOI: 10.1016/j.ejor.2012.05.006

► Liner ship fleet deployment with transshipment and transit time constraint. ► Container shipment demand varies from one week to the next. ► An efficient global optimization algorithm is proposed. This paper addresses a practical liner ship fleet deployment problem with week-dependent container shipment demand and transit time constraint, namely, maximum allowable transit time in container routing between a pair of ports. It first uses the space–time network approach to generate practical container routes subject to the transit time constraints. This paper proceeds to formulate the fleet deployment problem based on the practical container routes generated. In view of the intractability of the formulation, two relaxation models providing lower bounds are built: one requires known container shipment demand at the fleet deployment stage, and the other assumes constant container shipment demand over the planning horizon. An efficient global optimization algorithm is subsequently proposed. Extensive numerical experiments on the shipping data of a global liner shipping company demonstrate the applicability of the proposed model and algorithm.