【摘要】：多式聯(lián)運(yùn)在全球化貿(mào)易和國際集裝箱運(yùn)輸?shù)目焖侔l(fā)展下應(yīng)運(yùn)而生,在全球化節(jié)能降耗、運(yùn)輸結(jié)構(gòu)多元化和以公路運(yùn)輸為典型的交通擁堵嚴(yán)峻化等趨勢下迅猛發(fā)展。多式聯(lián)運(yùn)通過合理組合各運(yùn)輸方式,發(fā)揮各運(yùn)輸方式的優(yōu)勢,能有效降低運(yùn)輸費(fèi)用和時(shí)間,是銜接物流活動(dòng)的關(guān)鍵,對于提升服務(wù)水平、緩解交通擁堵和降低環(huán)境污染等具有重要意義。 運(yùn)輸環(huán)境,特別是擁堵環(huán)境,其不確定性特征對運(yùn)輸決策有重要的影響。多式聯(lián)運(yùn)企業(yè)為獲取最大利益,必然需要在運(yùn)輸過程中,依據(jù)運(yùn)輸環(huán)境的變化改進(jìn)運(yùn)輸方案。因此,本文以模糊擁堵環(huán)境作為多式聯(lián)運(yùn)的運(yùn)輸環(huán)境,對其運(yùn)輸決策問題進(jìn)行了動(dòng)態(tài)優(yōu)化研究。 控制論是在運(yùn)動(dòng)和發(fā)展中考察系統(tǒng),將其應(yīng)用于運(yùn)輸決策,能確保運(yùn)輸過程的可控化和決策方案的精準(zhǔn)化。本文以過程控制的思想,針對多式聯(lián)運(yùn)運(yùn)輸決策的靜態(tài)優(yōu)化方法的不足：運(yùn)輸環(huán)境固定化、運(yùn)輸信息不精確、缺乏對運(yùn)輸風(fēng)險(xiǎn)的掌控、優(yōu)化方案與實(shí)際不符等,提出了基于過程控制的運(yùn)輸決策動(dòng)態(tài)優(yōu)化方法。通過分析模糊擁堵運(yùn)輸環(huán)境下運(yùn)輸過程的特點(diǎn)和影響運(yùn)輸決策的因素,構(gòu)建了面向客戶滿意度和運(yùn)輸成本的模糊機(jī)會約束規(guī)劃模型；在此基礎(chǔ)上,設(shè)計(jì)了過程控制優(yōu)化方案；根據(jù)運(yùn)輸過程,引入了基于運(yùn)輸決策階段的分置過程控制環(huán)節(jié),控制各階段的實(shí)時(shí)運(yùn)輸信息的更新操作；提出了運(yùn)輸決策的過程控制策略及其執(zhí)行準(zhǔn)則,實(shí)現(xiàn)對最優(yōu)運(yùn)輸方案的動(dòng)態(tài)調(diào)整；最后,設(shè)計(jì)了基于運(yùn)輸過程控制的粒子群算法求解運(yùn)輸決策動(dòng)態(tài)優(yōu)化模型。 通過算例仿真與分析,驗(yàn)證了過程控制下的優(yōu)化方法以及求解算法的有效性。結(jié)果表明：過程控制動(dòng)態(tài)優(yōu)化下的運(yùn)輸方案的優(yōu)于靜態(tài)優(yōu)化下的最優(yōu)方案；在運(yùn)輸決策中考慮擁堵環(huán)境,降低了運(yùn)輸費(fèi)用和時(shí)間,平衡了各運(yùn)輸方式的擁堵壓力；從過程控制的角度進(jìn)行優(yōu)化,提高了在運(yùn)輸過程中的應(yīng)急響應(yīng)效率,減少了運(yùn)輸?shù)耐獠砍杀?能為運(yùn)輸企業(yè)對運(yùn)輸方案進(jìn)行過程控制提供決策支持。
[Abstract]:Multimodal transport emerges as the times require with the rapid development of global trade and international container transportation. It develops rapidly under the trend of globalization, energy saving and consumption reduction, diversification of transport structure and severe traffic congestion, which is typical of road transportation. Multimodal transport can effectively reduce transport costs and time by reasonably combining various modes of transport, giving full play to the advantages of each mode of transport, and is the key to linking up logistics activities. It is of great significance to alleviate traffic congestion and reduce environmental pollution. The uncertain characteristics of transport environment, especially congested environment, play an important role in transportation decision-making. In order to obtain the maximum benefit, the multimodal transport enterprise must improve the transportation scheme according to the change of transportation environment in the course of transportation. Therefore, in this paper, the fuzzy congestion environment is used as the transport environment of multimodal transport, and the dynamic optimization of its transport decision problem is studied. Cybernetics is to investigate the system in motion and development, and to apply it to transportation decision making, which can ensure the control of transportation process and the precision of decision scheme. Based on the idea of process control, this paper aims at the shortcomings of static optimization methods of multimodal transport decision, such as immobilization of transportation environment, imprecision of transportation information, lack of control of transportation risk, lack of optimization scheme and so on. A dynamic optimization method for transportation decision making based on process control is proposed. Based on the analysis of the characteristics of the transportation process and the factors influencing the transportation decision in the environment of fuzzy traffic congestion, a fuzzy opportunity-constrained programming model for customer satisfaction and transportation cost is constructed, and the optimization scheme of process control is designed. According to the transportation process, the separate process control link based on the transportation decision stage is introduced to control the update operation of the real-time transportation information in each stage. The process control strategy of transportation decision and its execution criterion are put forward to realize the dynamic adjustment of the optimal transportation scheme. Finally, the particle swarm optimization algorithm based on transport process control is designed to solve the dynamic optimization model of transportation decision. Through the simulation and analysis of an example, the effectiveness of the optimization method and the solution algorithm under the process control are verified. The results show that the transportation scheme under dynamic process control is better than that under static optimization, congestion environment is considered in transportation decision, transportation cost and time are reduced, and congestion pressure of each mode is balanced. From the point of view of process control, the efficiency of emergency response in transportation process is improved, the external cost of transportation is reduced, and the decision support is provided for transportation enterprise to carry out process control of transportation scheme.
【學(xué)位授予單位】：大連海事大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U116

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