A decision tree based decomposition method for oil refinery scheduling

查看全文 作　　者：Xiaoyong [1,2]Gao;Dexian [2]Huang;Yongheng [2]Jiang;Tao [3]Chen

机构地区：[1]Institute for Ocean Engineering, China University of Petroleum;[2]Department of Automation, Tsinghua University;[3]Department of Chemical and Process Engineering, University of Surrey

出　　处：《Chinese Journal of Chemical Engineering》索引2018年第26卷第8期,共8页

基　　金：Supported by the National Natural Science Foundation of China(21706282,21276137,61273039,61673236);Science Foundation of China University of Petroleum,Beijing(No.2462017YJRC028);the National High-tech 863 Program of China(2013AA 040702) 摘　　要：Refinery scheduling attracts increasing concerns in both academic and industrial communities in recent years.However, due to the complexity of refinery processes, little has been reported for success use in real world refineries. In academic studies, refinery scheduling is usually treated as an integrated, large-scale optimization problem,though such complex optimization problems are extremely difficult to solve. In this paper, we proposed a way to exploit the prior knowledge existing in refineries, and developed a decision making system to guide the scheduling process. For a real world fuel oil oriented refinery, ten adjusting process scales are predetermined. A C4.5 decision tree works based on the finished oil demand plan to classify the corresponding category(i.e. adjusting scale). Then,a specific sub-scheduling problem with respect to the determined adjusting scale is solved. The proposed strategy is demonstrated with a scheduling case originated from a real world refinery. 关键词：分解方法炼油厂学术研究优化问题精炼厂决策系统需求计划复杂性

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A decision tree based decomposition method for oil refinery scheduling

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