Study On The Vehicle Routing Optimizition Of Dangerous Goods

With the continuous development of chemical industry and modern science andtechnology, the variety and quantity of dangerous goods increase day by day. Due to thenumerous quantity and complicated hazardous characteristics, they cause serious threat to thepersonal satefy, property safety and ecological environment around the transportation road.The dangerous goods in enterprise must be transported on the specify route which aregenerally designated by the government directly, however, some transportation routes mayhave serious risk and hidden danger in actual vehicle routing.Scientific and reasonable vehiclerouting of dangerous goods can reduce this risk greatly, eliminate the hidden danger, so it isnecessary to study the vehicle routing problem of dangerous goods transportation.The vehicle routing problem of dangerous goods transportation under deterministicenvironment and uncertain environment are researched in this paper. This paper discusses theproblem under deterministic environment in two conditions.At first, this paper studies thesingle-source vehicle routing problem of dangerous goods transportation, minimizes thetransportation risk,transportation cost and transportation time, and considers service timewindow and maxmum risk limits, then the muti-objective optimization model isestablished,finally an improved muti-objective genetic algorithm is designed. Secondly, themuti-source vehicle routing problem of dangerous goods transportation is studied. Themaxmum risk limits and the vehicles returned to their respective source point are consideredin constraints, and the muti-objective optimization model is established, then a two-phaseheuristic algorithm is designed. The problem under uncertain environment is also discussedunder two different conditions.First,the single-source vehicle routing problem of dangerousgoods transportation is analyzed,road travel time as the uncertain parameters, time window,capacity of vehicle, demand as constraints, then the chance-constrained programming modelsfor this problem are build.In order to solve these models,a hybrid intelligent algorithm isdesigned based on the genetic algorithm and simulation technology.Then this paper analyzesthe muti-source vehicle routing problem of dangerous goods transportation. The chance-constrained programming models for this problem are established, and the improved heuristicalgorithm is used to solve these models. Finally, the reliability of models and the effectivenessof algorithms are verified through an example.The research results can reduce thetransportation risk, save the transportation cost, and improve the transportation efficiency,which have important significance for the development of dangerous goods transportation.