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Low Carbon Transportation Network Optimization Of Bulk Cargo Containerized Transportation

Posted on:2019-07-31Degree:MasterType:Thesis
Country:ChinaCandidate:H Y MiaoFull Text:PDF
GTID:2439330596465981Subject:Logistics management
Abstract/Summary:PDF Full Text Request
In the face of increasing energy consumption and increasingly serious environmental pollution problems,the transportation industry,as a major source of energy emissions,should shoulder the responsibility of slowing the greenhouse effect and transforming to low-carbon transport.Bulk transport occupies a place in transportation,but the traditional bulk cargo transport has the disadvantages of high freight rate of cargo damage,poor transport quality and serious environmental pollution.With the high quality and diversification of global grain,fertilizer and other bulk production,the traditional bulk transport mode has been unable to meet the demand of the market.In contrast,bulk containerized transportation has the advantages of high quality,high efficiency and environmental protection,etc.,and has certain advantages over bulk transport mode in terms of cost,time and efficiency.Some ports and enterprises have tried to transport goods such as coal and chemical fertilizers by container.Bulk container transport is gradually integrated into the bulk distribution system,and continues to grow and develop.However,from the current situation of enterprises developing bulk containerized transportation,there are problems such as low overall operation efficiency,high operating costs and aggravation of environmental pollution.In order to develop low carbon economy better and achieve mutual benefits between the environment and the economy,the enterprises should give consideration to the environmental impact while optimizing the transportation network.Therefore,it is of great theoretical and practical significance to study the optimization of multi-modal transport network for bulk containerized transportation in low carbon environment.Based on the background of the development of low carbon economy and bulk containerized transportation this paper analyzes the current situation,motivation and adaptation conditions of bulk containerized transportation,and clarifies the conditions and necessity for carrying out such transport.On this basis,this paper constructs a carbon emission calculation function by analyzing the influencing factors of carbon emissions and the carbon emissions of each transportation mode and transforms it into the carbon emission cost through the carbon tax.Furthermore,on the basis of analyzing the characteristics of various modes of transport,the cost of different modes in the transportation process is discussed in detail,including transportation cost,transit cost,transportation time cost and special cost of bulk containerized transportation.Therefore,the optimization model of the bulk containerized transportation network with the lowest total integrated transportation cost,including the above cost,is established.According to the characteristics of the model,the improved genetic algorithm with matrix coding and mixed selection is used to improve the performance and efficiency of the algorithm.The improved genetic algorithm based on matrix coding and hybrid selection is also proposed to improve the performance of the algorithm and its efficiency.Finally,using MATLAB software to simulate the import potash container transport of A company,and then respectively obtained different optimal transport networks consider the carbon emissions or not.Besides,the impact of transportation time limits and carbon tax prices on the optimization of transportation networks was analyzed.Analysis of the simulation results showed that by adding the carbon emission cost to the overall transportation cost,the company could achieve a win-win result of economic benefits and green transportation.The calculation results strongly confirmed the feasibility of the model and the effectiveness of the algorithm.
Keywords/Search Tags:bulk containerized transportation, low carbon, network optimization, multimodal transport, genetic algorithm
PDF Full Text Request
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