The simultaneous berth and quay crane allocation problem

碩士 === 海洋大學 === 商船學系所 === 96 === Review the record between 1996 to 2006 form Kaohsiung Harbor Bureau, these 10 years, the volume of each vessel arrived in Kaohsiung seaport is increasing. In 1996, the volume of arrived vessel (including all kind of vessel) is 17000 tons, and in 2006 the volume is ri...

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Bibliographic Details
Main Authors: Chia-Chen Hsieh, 謝佳珍
Other Authors: Ki-Yin Chan
Format: Others
Language:en_US
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/72565301296613400700
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Summary:碩士 === 海洋大學 === 商船學系所 === 96 === Review the record between 1996 to 2006 form Kaohsiung Harbor Bureau, these 10 years, the volume of each vessel arrived in Kaohsiung seaport is increasing. In 1996, the volume of arrived vessel (including all kind of vessel) is 17000 tons, and in 2006 the volume is rising to around 20000 tons of each vessel. Not only for this factor, compare with 1996 and 2006, we can also find out the number of import and export container is growing into 1.5 times in these 10 years. From the point of view, everyone seeks for ships for large size in the shipping market. Accordingly, in order to achieve a high productivity of hub port, effective and efficient terminal operations are mandatory and especially berth and quay crane allocation becomes very important. In this context, this dissertation addresses efficient berth and quay crane scheduling at a multi-user container terminal. In chapter one, we introduce the concept of berth allocation problem (BAP) and quay crane allocation (CAP) and their importance for terminal operations. In the following chapter we review existing literature of BAP and CAP. In chapter three, at first the formulation of BAP is introduced. For problem complexity, we make the formulation of simultaneous berth and quay crane allocation problem (B&CAP) by adding CAP related constraints to the BAP formulation. The most important assumption of this theory is that when the crane number is insufficient, the handling work will be not started. Then, the formulation would find out a suitable handling beginning time. Finally it would sum up the minimum of total service time. In chapter four, we discuss about the solution procedure. We develop a Genetic Algorithm-based heuristic to find an approximate solution for the B&CAP. The solution procedure of B&CAP is coded in C language. Chapter five discusses the computational experiments. The summary of analyses of the experiments follows: in general the total service time can decrease with more quay cranes being deployed, but this is not always the case, especially the terminal is not so busy with a fewer calling ships within a limited time. Analyzing the current situation of major container terminals, we can earn a large benefit by installing the B&CAP for these terminals.