發(fā)布時間：2018-11-14 16:48

【摘要】：集裝箱運輸的快速發(fā)展對集裝箱碼頭的作業(yè)效率要求越來越高。在集裝箱碼頭中與作業(yè)效率相關的泊位一直是稀缺資源,岸橋則是進行裝卸的主要設備。泊位與岸橋資源的合理利用,能夠有效的縮短船舶在港時間,提高碼頭的服務質量,實現港口效益的最大化。本文在歸納和評述大量相關文獻的基礎上,針對當前泊位、岸橋調度問題的研究現狀,發(fā)現目前該問題研究仍不夠理想。泊位與岸橋聯合調度研究需要進一步改善,基于泊位、岸橋的主輔碼頭靠泊決策協(xié)同優(yōu)化問題更是缺乏研究。本文針對上述幾方面的問題,做出如下研究工作： (1)考慮集裝箱碼頭現實約束,根據泊位資源動態(tài)配置的具體特征,利用排隊論的相關知識建立泊位資源動態(tài)配置模型,通過模擬迭代算法實現求解過程,實現泊位資源的動態(tài)配置。算例的實驗結果證明該模型適合碼頭作業(yè),具有良好的適應性。 (2)基于泊位資源動態(tài)配置的泊位計劃,實現泊位與岸橋聯合調度優(yōu)化,構建聯合調度模型,并通過遺傳算法進行求解。在算例分析中,將聯合調度優(yōu)化的結果與單獨優(yōu)化的結果進行對比,無論是作業(yè)效率還是空閑率,聯合優(yōu)化的結果具有高效性,模型和算法具有高效性。 (3)基于泊位資源動態(tài)配置、泊位與岸橋的聯合調度優(yōu)化,構建主輔碼頭靠泊決策協(xié)同優(yōu)化模型,在算法設計上,對遺傳算法進行改進。通過編程和仿真實驗,得出主輔碼頭靠泊決策以及轉運計劃,并通過對三種不同情形下的求解結果對比,算法能在較短的時間內收斂,證明了算法的有效性。
[Abstract]:With the rapid development of container transportation, the operational efficiency of container terminal is becoming more and more high. Berths related to operational efficiency in container terminals are always scarce resources, and quayside bridges are the main equipment for loading and unloading. The reasonable utilization of berth and shore bridge resources can effectively shorten the ship's time in port, improve the service quality of wharf, and realize the maximization of port benefit. On the basis of summarizing and reviewing a large number of related literatures, this paper finds that the current research on berth and quayside bridge scheduling problem is still not satisfactory. The research on joint dispatch of berth and quayside bridge needs further improvement. Based on berth, the cooperative optimization of berthing decision for main and auxiliary wharves is even less studied. In view of the above problems, this paper makes the following research work: (1) considering the practical constraints of container terminal, according to the specific characteristics of the dynamic allocation of berth resources, The dynamic allocation model of berth resources is established by using the relevant knowledge of queuing theory, and the dynamic allocation of berth resources is realized by simulating iterative algorithm. The experimental results show that the model is suitable for wharf operation and has good adaptability. (2) based on the berth plan of dynamic allocation of berth resources, the joint scheduling optimization of berth and quayside bridge is realized, and the joint scheduling model is constructed and solved by genetic algorithm. In the case study, the results of joint scheduling optimization are compared with those of single optimization. The results of joint optimization are efficient, and the model and algorithm are efficient, regardless of job efficiency or idle rate. (3) based on the dynamic allocation of berth resources and the joint scheduling optimization of berth and shore bridge, the cooperative optimization model of berthing decision for main and auxiliary wharves is constructed, and the genetic algorithm is improved in algorithm design. Through programming and simulation experiments, the berthing decision and transportation plan of the main and auxiliary wharf are obtained. By comparing the results of three different cases, the algorithm can converge in a short time, which proves the validity of the algorithm.
【學位授予單位】：大連海事大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：U656.135;U691

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本文編號：2331741