International Handbook of Maritime Economics
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International Handbook of Maritime Economics

Edited by Kevin Cullinane

This timely and comprehensive new Handbook brings together an unrivalled group of distinguished scholars and practitioners to provide in-depth analysis and a contemporary perspective on a wide-ranging array of topics in maritime economics.
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Chapter 14: Optimal Inventory Control for Empty Containers in a Port with Random Demands and Repositioning Delays

Dong-Ping Song and Qing Zhang


1 Dong-Ping Song and Qing Zhang 14.1 Introduction The ever-expanding global economy has led to the rapid growth of container shipping. Both supply (in terms of container vessel shipping capacity) and demand (in terms of world container throughput) have maintained double-digit annual growth rates. Large container vessels and large demand volumes put huge pressure on container ports. Many sea ports are struggling with their handling capacities. Not only do quayside lifting capacity and landside transportation capacity need to be increased, but also the port internal storage space should be expanded. To make things worse, due to the increasing imbalance and volatility of trade demands, shipping companies and port operators are facing challenges in managing container operations effectively in the shipping supply chain (Song et al., 2005). As containers occupy precious storage space in ports and many ports are constrained by their geographic infrastructure, a quicker turnaround time would be desirable. Because of the dynamic and stochastic nature of the container shipping business, a certain level of empty container inventory is often necessary to meet uncertain demands and avoid the higher cost of leasing empty containers from vendors. This chapter focuses on the issue of how to control the empty containers effectively in a port in a dynamic, stochastic and time-delay environment. Since the beginning of containerization in the 1950s, there have been a lot of studies on improving the management of container fleets. Many studies focused on deterministic systems using classical linear programming formulations (for example White, 1972; Dejax and...

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