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Scheduling of Container Handling Equipment in Marine Container Terminals

Narges Kaveshgar-2014-01-01-Scholar Commons (University of South Carolina)

TL;DRAbstract

To improve the competitiveness of marine container terminals, it is critical to minimize the makespan of a container vessel. The makespan is defined as the latest completion time among all handling tasks of the container vessel. Lower makespan (i.e. lower vessel turn time) can be achieved through better scheduling of the container handling equipment during vessel operations. The scheduling of terminal equipment is an operational problem, and a detailed schedule for each type of equipment operating in the terminal is necessary. Several studies have applied operations research techniques to optimize the processes of equipment in a terminal. This dissertation investigates three main operations in a marine container terminal, namely: quay crane scheduling, yard truck scheduling and yard crane scheduling. The first study in this dissertation addresses the quay crane scheduling problem (QCSP), which is known to be NP-hard. A genetic algorithm (GA) was developed and tested on several benchmar

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To improve the competitiveness of marine container terminals, it is critical to minimize the makespan of a container vessel. The makespan is defined as the latest completion time among all handling tasks of the container vessel. Lower makespan (i.e. lower vessel turn time) can be achieved through better scheduling of the container handling equipment during vessel operations. The scheduling of terminal equipment is an operational problem, and a detailed schedule for each type of equipment operating in the terminal is necessary. Several studies have applied operations research techniques to optimize the processes of equipment in a terminal. This dissertation investigates three main operations in a marine container terminal, namely: quay crane scheduling, yard truck scheduling and yard crane scheduling. The first study in this dissertation addresses the quay crane scheduling problem (QCSP), which is known to be NP-hard. A genetic algorithm (GA) was developed and tested on several benchmar

Keywords

Mathematical optimizationToolboxContainer (type theory)Scheduling (production processes)Benchmark (surveying)Computer scienceMATLABGenetic algorithm

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