Research On The Distribution Path For Product Oil In HuBei Transport Company CNPC

China National Petroleum Transport Company Hubei Branch ("Hubei Petroleum Transport Company") was founded in February 2003, is an specialized logistics company which integrated oil products, natural gas, aviation fuel and petrochemical products transportation and distribution. Existing 630 staffs,372 vehicles. Mainly provides distribution services from 13 oil depots to more than 750 gas stations and every airport in Hubei. Hubei Petroleum Transportation Company, although take a lot of refined oil’s work distribution, the problems that exist in the distribution path and distribution volume hinder the growth of corporate profits. Therefore, how to optimize refined oil’s distribution path and distribution volume, thereby reducing costs has become an important issue. The main results of this paper are as follows.Analyze the current situation in the oil distribution path and distribution volume of Hubei Petroleum Transport Company, summarize existing problems. Artificial distribution program have randomness, leading to the problems in the oil distribution in the Hubei Petroleum Transport Company. The problems are that loss costs increase caused by the irrational distribution volume from oil depots to gas stations; transportation costs increase caused by irrational vehicle scheduling; delay costs increase caused by not considering jams and restrictions, Through the collection and analysis of relevant 2013’s data,show that these problems have brought huge economic losses to the enterprise.For the problems existed in the refined oil distribution of Hubei Petroleum Transport Company, extract the elements of affecting transport cost and path arrangement, make the total costs (transportation costs from oil depots to gas stations+loss costs caused by insufficient oil +delay costs caused by serving not according to schedule time) minimal, the route optimization model is established to optimize oil distribution route, solving and give the distribution route and distribution volume. The results show that the model and algorithm given in the paper are effective, optimized distribution costs significantly less than non-optimized costs.