本文選題：海運(yùn)物流　切入點(diǎn)：場(chǎng)站—碼頭作業(yè)調(diào)度模型　出處：《哈爾濱工業(yè)大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：伴隨著全球經(jīng)濟(jì)一體化步伐的加快,世界各國(guó)間的貿(mào)易往來(lái)日益頻繁,跨地域商品交易量大幅增長(zhǎng),海運(yùn)物流作為當(dāng)今國(guó)際貿(mào)易往來(lái)的重要交通樞紐直接影響和制約著我國(guó)的經(jīng)濟(jì)增長(zhǎng),然而現(xiàn)有的海運(yùn)物流服務(wù)水平已經(jīng)很難滿足日益增長(zhǎng)的需求。如何通過(guò)對(duì)海運(yùn)物流終端節(jié)點(diǎn)場(chǎng)站、碼頭間的作業(yè)進(jìn)行有效地調(diào)度以實(shí)現(xiàn)對(duì)集裝箱進(jìn)行快速操作的目標(biāo),是解決該問(wèn)題的有效方法。集裝箱是海運(yùn)物流場(chǎng)站—碼頭作業(yè)調(diào)度的主要操作對(duì)象,如何在海運(yùn)物流場(chǎng)站—碼頭有限資源的條件下,有效協(xié)調(diào)各部分資源之間的關(guān)系,縮短船舶在港口的等待時(shí)間,有效地提高海運(yùn)物流場(chǎng)站—碼頭作業(yè)調(diào)度的服務(wù)水平是本文所需要解決的主要問(wèn)題。針對(duì)該問(wèn)題,本文提出了海運(yùn)物流場(chǎng)站—碼頭作業(yè)調(diào)度計(jì)劃方法。首先,針對(duì)海運(yùn)物流場(chǎng)站、碼頭當(dāng)中所具有的資源進(jìn)行分析和定義,其中包括岸橋裝卸服務(wù)資源的分析和定義,水平運(yùn)輸服務(wù)資源的分析和定義,場(chǎng)站裝卸設(shè)備服務(wù)資源的分析和定義,場(chǎng)站堆存服務(wù)資源的分析和定義,在此基礎(chǔ)上明確影響海運(yùn)物流場(chǎng)站—碼頭作業(yè)調(diào)度問(wèn)題的主要影響因素;其次,針對(duì)海運(yùn)物流場(chǎng)站—碼頭作業(yè)調(diào)度問(wèn)題進(jìn)行深入研究,并且建立該問(wèn)題各部分所對(duì)應(yīng)的數(shù)學(xué)模型�？紤]到海運(yùn)物流場(chǎng)站—碼頭作業(yè)調(diào)度問(wèn)題隸屬于大規(guī)模組合優(yōu)化的研究領(lǐng)域,使用傳統(tǒng)的優(yōu)化算法很難對(duì)此問(wèn)題進(jìn)行有效地求解,鑒于仿生智能優(yōu)化算法對(duì)該類問(wèn)題求解的良好表現(xiàn),本文針對(duì)問(wèn)題模型的離散性、動(dòng)態(tài)性和多目標(biāo)約束的特點(diǎn)對(duì)遺傳算法和人工蜂群算法進(jìn)行了有針對(duì)性的改進(jìn)以適應(yīng)對(duì)該問(wèn)題模型的求解,并且進(jìn)一步對(duì)兩種算法的求解結(jié)果進(jìn)行了對(duì)比,以證明模型的合理性和所提算法對(duì)問(wèn)題的求解性能;最后,針對(duì)所建立的模型和所使用的算法搭建一個(gè)原型系統(tǒng),對(duì)所建立的模型和所應(yīng)用的算法的求解結(jié)果給出更加直觀的表現(xiàn)形式。本文所搭建的原型系統(tǒng)針對(duì)海運(yùn)物流場(chǎng)站—碼頭的具體實(shí)例進(jìn)行設(shè)計(jì),通過(guò)模型庫(kù)、算法庫(kù)和業(yè)務(wù)處理模塊最后通過(guò)前端展示模塊對(duì)問(wèn)題求解結(jié)果、性能對(duì)比結(jié)果、優(yōu)化效果進(jìn)行可視化的直觀展示。
[Abstract]:With the acceleration of the pace of global economic integration, trade exchanges between countries in the world are becoming more and more frequent, and the volume of cross-regional commodity transactions has increased substantially. As an important transportation hub of international trade, maritime logistics directly affects and restricts the economic growth of our country. However, the existing service level of maritime logistics has been difficult to meet the increasing demand. How to effectively schedule the operations between terminals and terminals to achieve the goal of rapid operation of containers. Container is the main operation object of marine logistics station-wharf operation scheduling, how to coordinate the relationship between each part of resources effectively under the condition of limited resources of marine logistics station-wharf, Shortening the waiting time of the ship in the port and effectively improving the service level of the seaborne logistics station-wharf operation scheduling are the main problems to be solved in this paper. In this paper, the scheduling method of marine logistics station-wharf operation is put forward. Firstly, the analysis and definition of the resources in the terminal, including the analysis and definition of the loading and unloading service resources of the shore bridge, are carried out. Analysis and definition of horizontal transportation service resources, analysis and definition of station-handling equipment service resources, analysis and definition of stowage service resources at yard stations, On this basis, it is clear that the main factors that affect the operation scheduling problem of maritime logistics station-wharf. Secondly, the paper makes a deep research on the operation scheduling problem of marine logistics station-wharf. Considering that the scheduling problem belongs to the research field of large-scale combinatorial optimization, it is difficult to solve the problem effectively by using the traditional optimization algorithm. In view of the good performance of the bionic intelligent optimization algorithm for solving this kind of problem, this paper aims at the discreteness of the problem model. The dynamic and multi-objective constraints have improved the genetic algorithm and artificial bee colony algorithm to adapt to the solution of the problem model, and further compared the results of the two algorithms. In order to prove the rationality of the model and the performance of the proposed algorithm to solve the problem. Finally, a prototype system is built for the established model and the algorithm used. In this paper, the prototype system is designed for the specific example of marine logistics station-wharf, through the model base, Finally, the algorithm library and business processing module display the result of solving the problem through the front-end display module, compare the results of performance, and visualize the optimization effect.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：U691.3;U695.2;TP18

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本文編號(hào)：1556371