【摘要】：自2003年開(kāi)始,我國(guó)一直是世界鐵礦石的進(jìn)口第一大國(guó),長(zhǎng)期大批量的運(yùn)輸要求,促進(jìn)了我國(guó)鐵礦石專(zhuān)業(yè)化物流鏈的發(fā)展,沿海港口加速進(jìn)行專(zhuān)業(yè)化鐵礦石碼頭建設(shè),但是,依然滿足不了經(jīng)濟(jì)發(fā)展和鋼鐵工業(yè)的需要。那么只利用港口現(xiàn)有的資源,僅僅通過(guò)調(diào)度,不增加港口的設(shè)施設(shè)備,而能達(dá)到優(yōu)化資源、加快船舶裝卸、提高港口設(shè)備利用率和降低港口運(yùn)營(yíng)費(fèi)用,具有重大的意義。 論文以鐵礦石碼頭泊位調(diào)度為研究對(duì)象,首先從我國(guó)是世界上第一大鐵礦石進(jìn)口國(guó)的現(xiàn)實(shí),分析我國(guó)鐵礦石港口接卸能力與進(jìn)口總量的差距,引出論文研究的意義,結(jié)合國(guó)內(nèi)外研究現(xiàn)狀,提出論文的研究?jī)?nèi)容和方法。 其次,分析鐵礦石碼頭泊位調(diào)度的相關(guān)問(wèn)題,對(duì)論文要建立的模型進(jìn)行了簡(jiǎn)化,分析鐵礦石船舶卸船的流程,確定兩個(gè)優(yōu)化目標(biāo)函數(shù)。考慮船型不同的船舶,其待泊費(fèi)不同,指出以往很多研究以船舶在港時(shí)間最小為目標(biāo)的不足,確定船舶在港費(fèi)用最小的目標(biāo)函數(shù)；以船舶裝卸時(shí)產(chǎn)生的泊位運(yùn)營(yíng)費(fèi)用確定第二個(gè)目標(biāo)函數(shù),即最小化港口運(yùn)營(yíng)成本。 再次,概述遺傳算法的相關(guān)知識(shí),論文對(duì)基本遺傳算法的原理和流程作了相關(guān)綜述,論述了多目標(biāo)優(yōu)化用遺傳算法來(lái)實(shí)現(xiàn)的具體方法。 最后,設(shè)計(jì)鐵礦石碼頭泊位調(diào)度遺傳算法的具體實(shí)現(xiàn)過(guò)程�；谡撐难芯颗判騿�(wèn)題,采用自然數(shù)編碼；多目標(biāo)優(yōu)化通過(guò)權(quán)重系數(shù)法實(shí)現(xiàn),適應(yīng)度函數(shù)通過(guò)對(duì)目標(biāo)函數(shù)的轉(zhuǎn)換而得；選擇算子采用無(wú)放回余數(shù)隨機(jī)選擇,使用兩點(diǎn)交叉法進(jìn)行交叉,變異操作為換位變異；選擇相關(guān)控制參數(shù),對(duì)約束條件進(jìn)行處理；最后針對(duì)一個(gè)具體實(shí)例,運(yùn)行遺傳算法,驗(yàn)證算法有效性。
[Abstract]:Since 2003, China has been the largest import country of iron ore in the world. The long-term large quantity transportation requirements have promoted the development of the specialized logistics chain of iron ore in China, and the coastal ports have accelerated the construction of specialized iron ore wharves. Still can not meet the needs of economic development and iron and steel industry. Therefore, it is of great significance to utilize only the existing resources of the port, not to increase the facilities and equipments of the port, but to optimize the resources, speed up the loading and unloading of ships, improve the utilization ratio of port equipment and reduce the cost of port operation. The thesis takes the berth scheduling of iron ore terminal as the research object. Firstly, from the reality that our country is the largest iron ore importer in the world, this paper analyzes the gap between the iron ore port's unloading capacity and the total import quantity, and draws the significance of the paper's research. According to the present situation of domestic and international research, the research contents and methods of this paper are put forward. Secondly, the related problems of berth scheduling of iron ore terminal are analyzed, the model to be established is simplified, the process of unloading iron ore ship is analyzed, and two optimization objective functions are determined. Considering that different ship types have different berthing fees, it is pointed out that many previous researches have taken the minimum time of ship in port as the target to determine the objective function of the minimum cost of ship in port. The second objective function is to minimize port operation cost. Thirdly, the related knowledge of genetic algorithm is summarized, the principle and flow of basic genetic algorithm are summarized in this paper, and the specific method of realizing multi-objective optimization by genetic algorithm is discussed. Finally, the implementation process of genetic algorithm for berth scheduling of iron ore terminal is designed. Based on the research of sorting problem in this paper, natural number coding is adopted; multi-objective optimization is realized by weight coefficient method; fitness function is obtained by converting objective function; selection operator adopts random selection without retractive residue, Using the two-point crossover method, the mutation operation is transposition mutation; select the relevant control parameters to deal with the constraints; finally, for a specific example, run the genetic algorithm to verify the effectiveness of the algorithm.
【學(xué)位授予單位】：武漢理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類(lèi)號(hào)】：F252;F552;TP18

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 韓駿;孫曉娜;靳志宏;;集裝箱碼頭泊位與岸橋協(xié)調(diào)調(diào)度優(yōu)化[J];大連海事大學(xué)學(xué)報(bào);2008年02期

2 呂顯強(qiáng),張宏偉;集裝箱碼頭分派車(chē)輛的整數(shù)規(guī)劃模型[J];大連水產(chǎn)學(xué)院學(xué)報(bào);2004年02期

3 劉麗景;;遺傳算法與多Agent遺傳算法操作與性能比較[J];電腦知識(shí)與技術(shù);2011年16期

4 孟文君;杜麒棟;;我國(guó)鐵礦石碼頭通過(guò)能力與需求分析[J];中國(guó)港口;2009年10期

5 袁禮海,宋建社,畢義明,薛文通;混合遺傳算法及與標(biāo)準(zhǔn)遺傳算法對(duì)比研究[J];計(jì)算機(jī)工程與應(yīng)用;2003年12期

6 司曉悅,婁成武;從國(guó)際鐵礦石漲價(jià),看中國(guó)鋼鐵產(chǎn)業(yè)可持續(xù)發(fā)展[J];金屬礦山;2005年05期

7 劉動(dòng);;近年我國(guó)進(jìn)口鐵礦石的現(xiàn)狀與分析[J];金屬礦山;2009年01期

8 楊春霞;王諾;;基于多目標(biāo)遺傳算法的集裝箱碼頭泊位—岸橋分配問(wèn)題研究[J];計(jì)算機(jī)應(yīng)用研究;2010年05期

9 童珊;;基于船舶優(yōu)先權(quán)的集裝箱港口泊位分配問(wèn)題[J];交通運(yùn)輸工程與信息學(xué)報(bào);2012年01期

10 張佳運(yùn);盧剛;;集裝箱碼頭連續(xù)泊位動(dòng)態(tài)分配優(yōu)化模型及算法[J];北方交通;2011年04期

相關(guān)博士學(xué)位論文 前1條

1 胡一波;求解約束優(yōu)化問(wèn)題的幾種智能算法[D];西安電子科技大學(xué);2009年

相關(guān)碩士學(xué)位論文 前10條

1 葉賽男;基于Multi-Agent 的港口調(diào)度系統(tǒng)研究[D];北京交通大學(xué);2011年

2 陳歡;集裝箱場(chǎng)橋調(diào)度及其仿真研究[D];武漢理工大學(xué);2011年

3 候春霞;集裝箱碼頭出口箱堆場(chǎng)空間分配研究[D];大連海事大學(xué);2011年

4 張燕濤;基于遺傳算法的泊位調(diào)度問(wèn)題優(yōu)化研究及仿真[D];武漢理工大學(xué);2005年

5 魏璽杰;基于Agent的后方堆場(chǎng)機(jī)械調(diào)度模擬建模研究[D];大連海事大學(xué);2007年

6 姚夏莉;礦石碼頭裝卸工藝系統(tǒng)設(shè)備配置仿真優(yōu)化[D];大連理工大學(xué);2007年

7 黃鑫樂(lè);基于遺傳算法的鐵礦石碼頭泊位配置仿真優(yōu)化方法的應(yīng)用研究[D];上海海事大學(xué);2007年

8 代麗利;基于廣義遺傳算法的泊位分配問(wèn)題優(yōu)化研究[D];大連海事大學(xué);2008年

9 石春玲;港口作業(yè)調(diào)度的算法設(shè)計(jì)與模型研究[D];山東科技大學(xué);2008年

10 柴志剛;集裝箱碼頭泊位調(diào)度多目標(biāo)優(yōu)化方法研究[D];大連海事大學(xué);2009年

，

本文編號(hào)：2125879