Abstract
Cranes are central to port operations where cargo throughput and port efficiency is often determined by how well loading and unloading is performed. In ports, the effectiveness of any logistics management system which includes operating cranes is often impacted by pressures of limited port size, high cargo transshipment volumes and limited physical facilities and equipment [6]. It is therefore not surprising that emphasis has been placed on efficient crane scheduling in many ports, including the Port of Singapore [1], the Port of Hong Kong [8] and Australian ports [4].
Cranes are at the interface between land and sea, and because of operating space boundaries and crane structures cranes can only move in a limited areas, usually in one dimension along tracks. A typical operating scheme for quay cranes is illustrated as follows. Containers on vessels to be unloaded are usually partitioned into non-preemptive job parcels in some order on ship decks or holds and are moved to vehicles which transport them to stack yards for storage. In the reverse operation, cargo is loaded onto the ships from trucks out of yards. In this scenario, cranes and vehicles move through fixed channels or routes and bottlenecks occur when movement along these routes becomes congested [5].
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Lim, A., Rodrigues, B., Xu, Z. (2004). Solving the Crane Scheduling Problem Using Intelligent Search Schemes. In: Wallace, M. (eds) Principles and Practice of Constraint Programming – CP 2004. CP 2004. Lecture Notes in Computer Science, vol 3258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30201-8_59
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DOI: https://doi.org/10.1007/978-3-540-30201-8_59
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