【摘要】：隨著軍事格局的日益變化,建造可以長(zhǎng)時(shí)間在海上航行的大型船舶的需求愈來(lái)愈多。物資補(bǔ)給是影響此類(lèi)船舶續(xù)航能力和機(jī)動(dòng)性的重要因素,在較短的時(shí)間完成物資補(bǔ)給對(duì)于海上航行的大型船舶而言顯得尤為重要,研究物資補(bǔ)給理論搬運(yùn)時(shí)間優(yōu)化問(wèn)題、探討優(yōu)化模型和計(jì)算方法,具有重要的理論和現(xiàn)實(shí)意義。本文以某大型船舶物資補(bǔ)給為背景,建立理論搬運(yùn)時(shí)間優(yōu)化模型,主要從轉(zhuǎn)運(yùn)環(huán)節(jié)物流量控制和轉(zhuǎn)運(yùn)策略選擇兩個(gè)方面對(duì)物資補(bǔ)給過(guò)程進(jìn)行優(yōu)化,其決策目標(biāo)是使搬運(yùn)時(shí)間最短。從物資種類(lèi)和補(bǔ)給口數(shù)量?jī)蓚�(gè)因素來(lái)抽象物資補(bǔ)給過(guò)程,將優(yōu)化問(wèn)題分為單物資單補(bǔ)給口、單物資雙補(bǔ)給口、多物資單補(bǔ)給口、多物資雙補(bǔ)給口四種情形。對(duì)于單物資補(bǔ)給情形,歸結(jié)為網(wǎng)絡(luò)最大流問(wèn)題,采用Ford-Fulkerson算法進(jìn)行計(jì)算優(yōu)化,最大化系統(tǒng)流量,意即搬運(yùn)時(shí)間最短。對(duì)于多物資補(bǔ)給情形,優(yōu)化內(nèi)容為碼頭至船舶混合發(fā)貨的組合方案,即轉(zhuǎn)運(yùn)策略,此種情形屬于NP-hard問(wèn)題,與車(chē)間調(diào)度問(wèn)題類(lèi)似,基于事件驅(qū)動(dòng)思想,建立了優(yōu)化模型,以碼頭到船舶的混合發(fā)貨方案為變量,以搬運(yùn)時(shí)間最小為目標(biāo)函數(shù);采用遺傳算法進(jìn)行求解,對(duì)變量進(jìn)行矩陣編碼,并提出矩陣轉(zhuǎn)換方式使交叉之后產(chǎn)生的非法染色體合法化。由于標(biāo)準(zhǔn)遺傳算法容易陷入局部最優(yōu)且收斂較慢,本文在標(biāo)準(zhǔn)遺傳算法的基礎(chǔ)上進(jìn)行改進(jìn)。最后以某一具體實(shí)例為背景,驗(yàn)證了本文模型和算法的有效性,也證明了改進(jìn)遺傳算法較標(biāo)準(zhǔn)遺傳算法能得到更好的解并加快收斂速度。
[Abstract]:With the increasing change of military pattern, there is more and more demand for the construction of large ships that can sail at sea for a long time. Material supply is an important factor affecting the endurance and maneuverability of this kind of ship. It is particularly important for large ships sailing at sea to complete the material supply in a relatively short time. The optimization of material supply theory handling time is studied. It is of great theoretical and practical significance to discuss the optimization model and calculation method. Based on the material supply of a large ship, this paper establishes a theoretical transportation time optimization model, which mainly optimizes the material supply process from two aspects: the flow control of the transfer link and the selection of the transportation strategy. Its decision-making goal is to minimize the handling time. The process of material supply is abstracted from the two factors of material type and supply port quantity. The optimization problem is divided into four cases: single material single supply port, single material double supply port, multi-material single supply port and multi-material double supply port. For the case of single material supply, the problem of network maximum flow is reduced to the problem of network maximum flow. Ford-Fulkerson algorithm is used to optimize the calculation and maximize the system traffic, that is to say, the handling time is the shortest. For the case of multi-material supply, the optimization content is the combination scheme of mixed shipment from wharf to ship, that is, the transportation strategy, which belongs to the NP-hard problem, which is similar to the job shop scheduling problem. Based on the event-driven idea, the optimization model is established. The mixed shipping scheme from wharf to ship is taken as the variable, and the minimum handling time is taken as the objective function. Genetic algorithm is used to solve the problem, the variables are encoded by matrix, and the matrix transformation method is proposed to legitimize the illegal chromosomes after crossing. Because the standard genetic algorithm is easy to fall into local optimization and the convergence is slow, this paper improves on the basis of the standard genetic algorithm. Finally, based on a specific example, the effectiveness of the model and algorithm is verified, and it is proved that the improved genetic algorithm can get better solution and accelerate the convergence speed than the standard genetic algorithm.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類(lèi)號(hào)】：U693

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