陸港零擔(dān)貨運(yùn)三維裝箱與車(chē)輛調(diào)度集成優(yōu)化研究
發(fā)布時(shí)間：2018-10-15 15:56
【摘要】：零擔(dān)貨物運(yùn)輸是指貨主需要運(yùn)送的貨不足裝滿(mǎn)一個(gè)集裝箱，作為零星貨物交運(yùn)，承運(yùn)部門(mén)將不同貨主的貨物湊整一箱后再發(fā)運(yùn)的運(yùn)輸服務(wù)形式，具有來(lái)源分散，，流向分散的特點(diǎn)。傳統(tǒng)作業(yè)模式下，為保證集裝箱及運(yùn)輸車(chē)輛的容積和載重利用率，承運(yùn)部門(mén)根據(jù)目的地將托運(yùn)訂單分類(lèi)，等待同一目的地的零擔(dān)貨物集滿(mǎn)一箱后進(jìn)行運(yùn)輸；為減少存儲(chǔ)成本，承運(yùn)人希望盡早將零擔(dān)貨物交付收貨方。 陸港零擔(dān)貨運(yùn)與傳統(tǒng)零擔(dān)貨運(yùn)有明顯區(qū)別，首先，其托運(yùn)訂單有明確的交付時(shí)間規(guī)定；其次，托運(yùn)訂單的目的地為沿海港口，存儲(chǔ)費(fèi)用遠(yuǎn)高于陸港，且貨物提前運(yùn)抵須由陸港運(yùn)營(yíng)商承擔(dān)存儲(chǔ)費(fèi)用。為此，本文提出對(duì)托運(yùn)訂單進(jìn)行集中處理，將同一港口群中不同目的港的貨物拼箱運(yùn)輸，同時(shí)盡可能延遲其運(yùn)輸時(shí)間的優(yōu)化策略。與傳統(tǒng)零擔(dān)貨運(yùn)只進(jìn)行裝箱優(yōu)化不同，陸港零擔(dān)貨運(yùn)還需要考慮車(chē)輛指派、路徑優(yōu)化以及運(yùn)輸時(shí)間安排問(wèn)題。所以，陸港零擔(dān)貨運(yùn)優(yōu)化問(wèn)題是一個(gè)三維裝箱與車(chē)輛調(diào)度的集成優(yōu)化問(wèn)題。 為求解上述問(wèn)題，本文提出了陸港零擔(dān)貨運(yùn)三維裝箱與車(chē)輛調(diào)度集成優(yōu)化機(jī)制，并建立了相應(yīng)的集成優(yōu)化模型，尋找貨物、集裝箱、運(yùn)輸車(chē)輛以及運(yùn)輸時(shí)間的最優(yōu)組合方式。同時(shí)設(shè)計(jì)了主-從混合遺傳算法進(jìn)行實(shí)現(xiàn)。算法中，主級(jí)遺傳算法通過(guò)矩陣編碼表示貨物、集裝箱、運(yùn)輸車(chē)輛與運(yùn)輸時(shí)間的各種組合方式，從級(jí)啟發(fā)式染色體評(píng)價(jià)算法首先把染色體中基因型的解轉(zhuǎn)化為實(shí)際作業(yè)中表現(xiàn)型的解，并對(duì)不同情況的違約染色體分別進(jìn)行修復(fù)或懲罰處理，從而對(duì)其適應(yīng)度進(jìn)行評(píng)價(jià)；主級(jí)遺傳算法根據(jù)從級(jí)算法返回的個(gè)體適應(yīng)度值繼續(xù)進(jìn)行遺傳操作，多次迭代后得到問(wèn)題的近似最優(yōu)解。 最后，本文用MATLAB7.0進(jìn)行編程，通過(guò)數(shù)據(jù)對(duì)比實(shí)驗(yàn)，證實(shí)了集成優(yōu)化模型在集裝箱使用數(shù)量、車(chē)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(xué)位授予單位】：河北工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：U492.22;U492.33
本文編號(hào)：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(xué)位授予單位】：河北工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：U492.22;U492.33
【參考文獻(xiàn)】
相關(guān)期刊論文 前1條
1 于曉義;孫樹(shù)棟;褚崴;;基于并行協(xié)同進(jìn)化遺傳算法的多協(xié)作車(chē)間計(jì)劃調(diào)度[J];計(jì)算機(jī)集成制造系統(tǒng);2008年05期
本文編號(hào)：2273036
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