Research progress of refined oil first logistics optimization

In China, the research on the optimization of refined oil first logistics is currently at the very beginning stage, so its optimization space is large. In this paper, based on the refined oil first logistics optimization system in China, the research status of global refined oil first logistics optimization was analyzed systematically from the aspects of the related optimization mathematical models and their application, objective functions and solving methods. Then, the basic framework and further research directions of refined oil first logistics optimization were proposed based on China's national conditions. It is shown that the research trend and application of the optimization mathematical model are mainly concentrated on the deterministic mixed integer programming and the uncertain stochastic programming. The former is developed from the single-scheduling to the multi-scheduling mode, from the single-product to the multi-product and from the single-cycle to the multi-cycle, while the later is improved gradually from the discrete variables to the continuous variables with probability density, from the single-factor uncertainty to the multi-factor uncertainty and from the single-scene to the multi-scene. The minimum logistics cost function and the maximum production-transportation-distribution overall profit function are the optimization objective functions that are the most commonly used in the present research or practical application. The solving method for the model is mature, and it is extremely urgent to develop application software of logistics optimization secondarily or independently in accordance with domestic conditions.