Research On Location-distribution Problem For An Oil Company Based On Bi-level Programming Model

The benign development of the oil industry is a key link and an important engine to ensure the sustained growth of our national economy.In recent years,with the complicated new geopolitical situation and the impact of the COVID-19,the international oil market environment has become more complex and the competition in the domestic refined oil products sales industry has become more intense.Therefore,an in-depth study of the location-distribution problem of oil sales companies is of great practical significance to improve the time and efficiency of secondary distribution of refined oil products,reduce logistics costs,enhance the core competitiveness of enterprises,and thus promote the long-term development of the company.The main research content of this paper is as follows:(1)Through the investigation and analysis of the current distribution situation of an oil sales company,the key factors affecting the continuous increase of the company’s distribution costs were identified,the scope of this paper was defined,the optimization principles of the secondary distribution logistics of refined oil products were designed,and the optimization plan for the location of the oil depot and the distribution path of refined oil products was formulated.(2)The location problem of the oil depots and the distribution route problem of refined oil products were jointly analyzed in this research and a bi-level programming model of location-distribution was established intending to minimize the total cost.The upper-level model of oil depot location selection was constructed by analyzing the construction and operation cost of the oil depot,the storage cost of the oil depot,etc.The lower-layer model for tanker truck distribution path optimization was constructed by taking the tanker information obtained from the upper-layer model as input and considering the transportation cost of tanker trucks,the loss cost in finished oil distribution,and the penalty cost due to the time window constraint.(3)To build the model,a genetic algorithm was designed.Firstly,the solution idea was designed according to the features of the constructed model andthe solution process was planned.Secondly,an improved genetic algorithm was designed to build the upper model,and the population was initialized by adding the Holton sequence to increase the diversity and randomness of the initial population,and the memory bank operation was used to store the outstanding population individuals for the purpose of accelerating the convergence speed to obtain the parameters such as the number and location of the oil depots.Thirdly,the lower model was built by using a genetic algorithm.Finally,the improved genetic algorithm was compared with two other algorithms to verify the superiority of the genetic algorithm designed in this research.(4)Case study.An oil sales company was taken as the research object,and the actual operation data of the company was collected.The bi-level programming model for the location selection of the oil depot and distribution of refined oil products of the company was solved through MATLAB software and using a genetic algorithm,and the optimal location-distribution schemes for the supply chain of the company were obtained;The scheme data with the current situation of distribution of the company were compared to prove the effectiveness of this scheme;Finally,a sensitivity analysis was conducted to identify the key factors affecting the company’s distribution costs and to inform the company’s sustainable development.