Dangerous Goods For Station Layout Optimization Based On Genetic Algorithm

In our country, Railway in dangerous goods transport plays an important role. Inpetrochemical enterprise, national defense military systems and the development ofthe aerospace, to people’s health, children’s education career in many aspects, such asto the dangerous goods. Demand due to the national conditions in the plannedeconomy period in our country, deal with a lot of dangerous goods stations isestablished. But with the reform and opening up, China’s petrochemical industryproductivity layout on the big bang. Dangerous goods for station layout is no longeradapt to the present in our country dangerous goods transport.Dangerous for station layout optimization, can meet the demand of dangerousfreight send possibility, reducing environmental pollution, promote our countrydangerous goods transport efficiency. So from different perspective, dangerous forstation layout optimization is the necessary way of railway transportation safety andeffective means, has a strong timeliness and necessity. therefore, Railway only speedup the process of the transport of dangerous goods logistics, optimizing the layout ofthe dangerous goods to stand, can in the dangerous goods transport marketcompetitiveness, firm their own position. of course, Railway capacity, the allocationof resources, determine the stand area and dangerous goods transport requirements forrailway dangerous goods station is important according to the macro layout, theunified planning.but railway Dangerous Goods Stations layout optimization is a backing of manyhardware and software, and is a very complex and large work. First of all, you need toconsider the condition of the equipment and facilities of the crisis do stand how good,the establishment of a multi-objective evaluation system, and the Transport ofDangerous Goods Stations of the need to stop or shut down effective shunt HandlingStation still retains. Secondly, this paper establishes the corresponding mathematicalmodel. This model is to protect the environment and the traffic investigation based onthe overall effect evaluation, based on local coverage and maximum coverage locationmodeling thought, Achieve the goal of multi-objective decision. Multi-objectivelocation-dispatch method is subdivided into five steps to three process. Step1: cleardanger for station layout optimization of decision attribute. Step2: do stand for dangerous quality evaluation. Step3: to lines of the characteristics of railwaydangerous goods transport used for the reference (such as how much o f freightvolume, safety situation and properties, etc.), find out what is to stop the closedprivate sidings and removed from the entire road network planning. Step4: select themode of transportation comprehensive evaluation mathematical model. Step5: set upto meet relevant dangerous goods transportation cost to the minimum, screening aftercrisis do accept to stop close danger do stand transferred volume to reduce to theminimum, maximum, environmental risk comprehensive efficiency maximum meetthe first four steps of multi-objective location assignment model.Among them, themodel of the target by three aspects: Goal one, demanders comprehensive efficiencyis the largest. Goal two, control the environmental risks. Goal three, danger do standcost control target.Due to the combination of genetic method to solve the problem of location–dispatch, after the analysis of the results found that the result of this method is moreaccurate; operation rate is faster than usual genetic algorithm. So this article willapply combined genetic algorithm to handle railway dangerous goods station layoutoptimization to solve multi-objective location-dispatch model, Finally through the c#program language to realize the above algorithm to a certain region.