陸港零擔貨運三維裝箱與車輛調(diào)度集成優(yōu)化研究
發(fā)布時間：2018-10-15 15:56
【摘要】：零擔貨物運輸是指貨主需要運送的貨不足裝滿一個集裝箱，作為零星貨物交運，承運部門將不同貨主的貨物湊整一箱后再發(fā)運的運輸服務形式，具有來源分散，，流向分散的特點。傳統(tǒng)作業(yè)模式下，為保證集裝箱及運輸車輛的容積和載重利用率，承運部門根據(jù)目的地將托運訂單分類，等待同一目的地的零擔貨物集滿一箱后進行運輸；為減少存儲成本，承運人希望盡早將零擔貨物交付收貨方。 陸港零擔貨運與傳統(tǒng)零擔貨運有明顯區(qū)別，首先，其托運訂單有明確的交付時間規(guī)定；其次，托運訂單的目的地為沿海港口，存儲費用遠高于陸港，且貨物提前運抵須由陸港運營商承擔存儲費用。為此，本文提出對托運訂單進行集中處理，將同一港口群中不同目的港的貨物拼箱運輸，同時盡可能延遲其運輸時間的優(yōu)化策略。與傳統(tǒng)零擔貨運只進行裝箱優(yōu)化不同，陸港零擔貨運還需要考慮車輛指派、路徑優(yōu)化以及運輸時間安排問題。所以，陸港零擔貨運優(yōu)化問題是一個三維裝箱與車輛調(diào)度的集成優(yōu)化問題。 為求解上述問題，本文提出了陸港零擔貨運三維裝箱與車輛調(diào)度集成優(yōu)化機制，并建立了相應的集成優(yōu)化模型，尋找貨物、集裝箱、運輸車輛以及運輸時間的最優(yōu)組合方式。同時設計了主-從混合遺傳算法進行實現(xiàn)。算法中，主級遺傳算法通過矩陣編碼表示貨物、集裝箱、運輸車輛與運輸時間的各種組合方式，從級啟發(fā)式染色體評價算法首先把染色體中基因型的解轉(zhuǎn)化為實際作業(yè)中表現(xiàn)型的解，并對不同情況的違約染色體分別進行修復或懲罰處理，從而對其適應度進行評價；主級遺傳算法根據(jù)從級算法返回的個體適應度值繼續(xù)進行遺傳操作，多次迭代后得到問題的近似最優(yōu)解。 最后，本文用MATLAB7.0進行編程，通過數(shù)據(jù)對比實驗，證實了集成優(yōu)化模型在集裝箱使用數(shù)量、車輛行駛里程、集裝箱載重和容積平均利用率以及作業(yè)成本等方面均優(yōu)于傳統(tǒng)優(yōu)化方法下產(chǎn)生的結(jié)果，證明了本文集成優(yōu)化模型及算法的有效性。
[Abstract]:Part-load cargo transportation refers to the transport service that the cargo owner needs to carry less than one container to be delivered as sporadic cargo, and the transportation department collects the goods of different cargo owners in a single case before shipping, and the source is scattered. The characteristic of dispersing flow. In the traditional operation mode, in order to ensure the volume and load utilization ratio of container and transport vehicle, the shipping department classifies the consignment order according to the destination, and waits for the carton of the same destination to be transported after the carton is full; in order to reduce the storage cost, The carrier hopes to deliver the cargoes to the receiving party as soon as possible. There is a clear difference between dry port cargoes and traditional cargoes. First, the consignment order has a definite delivery time. Secondly, the consignment order is destined for a coastal port, and the storage cost is much higher than that of a dry port. And the arrival of goods in advance shall be borne by the dry port operator storage charges. For this reason, this paper puts forward an optimized strategy of centralized processing of consignment orders, which can transport cargoes of different destination ports in the same port group and delay the transportation time as much as possible. Different from the traditional cargo-loading optimization, the assignment of vehicles, route optimization and transportation timing are also considered in dry ports. Therefore, the dry port partial cargo optimization problem is an integrated optimization problem of three-dimensional packing and vehicle scheduling. In order to solve the above problems, this paper presents an integrated optimization mechanism for 3D container loading and vehicle scheduling in dry ports, and establishes a corresponding integrated optimization model to find the optimal combination of cargo, container, transport vehicle and transportation time. At the same time, a master-slave hybrid genetic algorithm is designed. In the algorithm, the principal genetic algorithm uses matrix coding to express various combinations of goods, containers, transport vehicles and transportation time. From the step heuristic chromosome evaluation algorithm, the solution of genotype in chromosome is transformed into the solution of phenotype in practical work, and the chromosomes in different cases are repaired or punished respectively, and the fitness of chromosome is evaluated. The principal genetic algorithm continues to perform genetic operations according to the individual fitness value returned from the hierarchical algorithm, and the approximate optimal solution of the problem is obtained after multiple iterations. Finally, this paper uses MATLAB7.0 to program, through the data contrast experiment, confirmed the integration optimization model in the container usage quantity, the vehicle driving mileage, The results of container load and volume average utilization ratio and activity cost are better than those of traditional optimization method, which proves the effectiveness of the integrated optimization model and algorithm.
【學位授予單位】：河北工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U492.22;U492.33
本文編號：2273036
[Abstract]:Part-load cargo transportation refers to the transport service that the cargo owner needs to carry less than one container to be delivered as sporadic cargo, and the transportation department collects the goods of different cargo owners in a single case before shipping, and the source is scattered. The characteristic of dispersing flow. In the traditional operation mode, in order to ensure the volume and load utilization ratio of container and transport vehicle, the shipping department classifies the consignment order according to the destination, and waits for the carton of the same destination to be transported after the carton is full; in order to reduce the storage cost, The carrier hopes to deliver the cargoes to the receiving party as soon as possible. There is a clear difference between dry port cargoes and traditional cargoes. First, the consignment order has a definite delivery time. Secondly, the consignment order is destined for a coastal port, and the storage cost is much higher than that of a dry port. And the arrival of goods in advance shall be borne by the dry port operator storage charges. For this reason, this paper puts forward an optimized strategy of centralized processing of consignment orders, which can transport cargoes of different destination ports in the same port group and delay the transportation time as much as possible. Different from the traditional cargo-loading optimization, the assignment of vehicles, route optimization and transportation timing are also considered in dry ports. Therefore, the dry port partial cargo optimization problem is an integrated optimization problem of three-dimensional packing and vehicle scheduling. In order to solve the above problems, this paper presents an integrated optimization mechanism for 3D container loading and vehicle scheduling in dry ports, and establishes a corresponding integrated optimization model to find the optimal combination of cargo, container, transport vehicle and transportation time. At the same time, a master-slave hybrid genetic algorithm is designed. In the algorithm, the principal genetic algorithm uses matrix coding to express various combinations of goods, containers, transport vehicles and transportation time. From the step heuristic chromosome evaluation algorithm, the solution of genotype in chromosome is transformed into the solution of phenotype in practical work, and the chromosomes in different cases are repaired or punished respectively, and the fitness of chromosome is evaluated. The principal genetic algorithm continues to perform genetic operations according to the individual fitness value returned from the hierarchical algorithm, and the approximate optimal solution of the problem is obtained after multiple iterations. Finally, this paper uses MATLAB7.0 to program, through the data contrast experiment, confirmed the integration optimization model in the container usage quantity, the vehicle driving mileage, The results of container load and volume average utilization ratio and activity cost are better than those of traditional optimization method, which proves the effectiveness of the integrated optimization model and algorithm.
【學位授予單位】：河北工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U492.22;U492.33
【參考文獻】
相關期刊論文 前1條
1 于曉義;孫樹棟;褚崴;;基于并行協(xié)同進化遺傳算法的多協(xié)作車間計劃調(diào)度[J];計算機集成制造系統(tǒng);2008年05期
本文編號：2273036
本文鏈接：http://www.wukwdryxk.cn/kejilunwen/jiaotonggongchenglunwen/2273036.html
教材專著
