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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/16281

Title: 船席與橋式起重機之同時排程問題研究
The simultaneous berth and quay crane allocation problem
Authors: Chia-Chen Hsieh
謝佳珍
Contributors: NTOU:Department of Merchant Marine
海洋大學:商船學系所
Keywords: 船席;橋式起重機;基因演算法;排程;在港時間
Berth allocation;Crane scheduling;GA;BAP;service time;CAP
Date: 2008
Issue Date: 2011-06-30T08:35:08Z
Abstract: 回顧高雄港務局之統計資料,從西元1996年至2006年這十年之間,靠港船舶之噸位明顯上升中。在1996年一年之中,藉由靠港船舶之總噸位除以船舶總數,將可發現平均每艘船舶之噸位約在17000噸之間 (包含各種不同船型) 。到了西元2006年時,此平均數值攀升至20000噸。除此之外,進出口的總貨櫃數量也在這十年間增加了1.5倍之多。從這些觀點看來,海運市場確實逐漸朝向大型化船舶經營模式。為了能提高港口之生產效率,將港邊的各項作業作最有效率之運用式本文之研究目的,其中船席以及橋式起重機的配置議題相當重要,因此本文著重於船席與橋式起重機排程問題之研究探討。   第一章中,我們介紹了船席配置和橋式起重機配置之觀念,以及其對於碼頭作業之重要性。第二章則回顧先前相關之文獻。 第三章提出船席排程之推導公式,並且為了接近實際作業中的複雜性,我們增加了新的橋式起重機排程限制式,使得原先在數學規劃中僅包含船席配置,而更添加了橋式起重機之配置模式考量。本文最重要的假設就是當船舶所需之橋式起重機數量無法滿足時,船舶之裝卸作業將無法啟動,直到找到適當的作業開始時間,並滿足所需之橋式起重機,經解算後求出在港總時間之最小值。 在第四章中,我們藉由基因演算法之理論,將此數學規劃以C語言撰寫程式完成。第五章則是討論電腦演算之結論,經由實驗證明,當船舶到港時間分布不同之情況下,並非在港口安置越多的橋式起重機,就能夠縮短全體船舶的在港總時間。惟有對於港口流量現況加以分析,才能夠真正發揮船席與橋式起重機之最大效益。
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.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0M92710006
http://ntour.ntou.edu.tw/ir/handle/987654321/16281
Appears in Collections:[商船學系] 博碩士論文

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