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Research Of Decision Making Method Of Yard Allocation In The General Cargo Terminal

Posted on:2018-10-06Degree:MasterType:Thesis
Country:ChinaCandidate:X X DengFull Text:PDF
GTID:2392330605953500Subject:Logistics technology and equipment
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With the advent and development of container transportation,the proportion of general cargo in the port is greatly compressed.However,due to the unique characteristic of general cargo,general cargo transportation cannot be substituted.Given the current level of China economic development,some various relatively cheap,low-margin general cargos and large quantities of steel goods is not suitable for container transportation,and general cargo terminals still remain the advantage.In one of the northern general cargo terminal,the storage strategy adopted is relatively casual,location assignment decision is mainly based on artificial experience,at the same time,because of the complexity of cargo operation system,and there are few related research literatures.Therefore,it is of great theoretical and practical significance to study the distribution decision of the general cargo terminal yard.System simulation and optimization methods are used to study the problem of stocking and cargo allocation.Firstly,based on the analysis of the characteristics of the loading and unloading operation system of the general cargo terminal,the simulation software is used to build the simulation model of the loading and unloading operation system.Secondly,three storage strategies are designed from different angles,and based on the simulation model,simulation test is carried out to evaluate and select the storage strategy.Then,based on the theory of rectangle layout,with the aim of maximizing the utilization of yard,the model of storage location assignment is established,and the particle swarm optimization algorithm is used to solve the problem.Finally,the validity of the model and algorithm is verified by practical examples.
Keywords/Search Tags:general cargo terminal, yard, simulation, storage strategy, storage location assignment, particle swarm optimization
PDF Full Text Request
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