成品油一次物流优化研究进展

Research progress of refined oil first logistics optimization

目前,我国成品油一次物流优化研究处于起步阶段,优化空间较大。基于我国的成品油一次物流优化体系,从成品油一次物流相关的优化数学模型与应用、目标函数及求解方法方面,系统分析了国内外成品油一次物流优化研究现状,提出符合我国国情的成品油一次物流优化基础框架和进一步研究方向。研究结果表明:成品油一次物流优化数学模型的研究趋势和应用主要集中在确定性混合整数规划和不确定性随机规划,前者从单一调运方式向多调运方式、单产品向多产品、单周期向多周期发展,后者从离散变量向概率密度连续变量、单因素不确定向多因素不确定、单一情景向多情景不断改进;物流成本最低函数和产运销整体利润最大函数是目前研究或实际应用中最常采用的优化目标函数;模型求解方法已经比较成熟,二次开发或完全自主开发符合我国国情的物流优化应用软件迫在眉睫。

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.