基于過(guò)程控制的貨物多式聯(lián)運(yùn)運(yùn)輸決策動(dòng)態(tài)優(yōu)化研究
[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(jí)別】:碩士
【學(xué)位授予年份】:2014
【分類(lèi)號(hào)】:U116
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