Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.588864
Title: Modelling of quayside logistics problems at container terminals
Author: Luo, Jiabin
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2013
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Abstract:
Container terminals serve as an interface between marine and land transportation. Since the introduction of containerisation in 1960s, the number of containers handled worldwide has dramatically grown every year. With the increasing containerisation, nowadays container terminals are working at maximum capacity. Therefore, the efficiency of stacking and transportation of large number of containers to and from the quayside is critical to any container terminal. We have investigated the integration of container-handling equipment (such as quay cranes, yard cranes, automated guided vehicles and straddle carriers) scheduling and container storage allocation problems in two types of container-handling system: one is automated container terminal, which represents the current container terminal development and the other is straddle-carrier system, which has been used by most European container terminals. For each type of container terminal, we have studied three integrated problems respectively considering container unloading process (during which containers are unloaded from a ship and delivered to the storage yard), container loading process (during which containers are picked up from the yard and delivered to the quayside to be loaded onto a ship) and dual-cycle process (unloading and loading of containers simultaneously). Our aims are to determine the optimal schedules of container-handling equipment and assign optimal yard locations for containers. The objective is to minimise the berth time of the ship, which is the most important factor to evaluate the efficiency of container terminals. We have developed six models for the above problems. Optimal solutions can be obtained in small sizes of the problems under investigation; however, large-sized problems are hard to solve optimally in a reasonable time. Therefore, genetic algorithms are designed for each model to solve the problem in large sizes. The computational results show the effectiveness of the proposed models and heuristic approaches in dealing with problems in container terminals.
Supervisor: Wu, Yue Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.588864  DOI: Not available
Keywords: HE Transportation and Communications ; HF Commerce ; TA Engineering (General). Civil engineering (General)
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