Enterprise-wide optimization of integrated planning and scheduling for refinery-petrochemical complex with heuristic algorithm

作     者：Lifeng Zhang Haoyang Hu Zhiquan Wang Zhihong Yuan Bingzhen Chen Lifeng Zhang;Haoyang Hu;Zhiquan Wang;Zhihong Yuan;Bingzhen Chen

作者机构：State Key Laboratory of Chemical EngineeringDepartment of Chemical EngineeringTsinghua UniversityBeijing 100084China Department of Chemical EngineeringTsinghua UniversityBeijing 100084China 

出 版 物：《Frontiers of Chemical Science and Engineering》 (化学科学与工程前沿(英文版))

年 卷 期：2023年第17卷第10期

页      面：1516-1532页

核心收录：

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：The authors gratefully acknowledge the financial support from the National Key Research and Development Program of China(Grant No.2018AAA0101602) 

主　　题：planning scheduling refinery-petrochemical convolutional neural network heuristic algorithm 

摘      要：This paper focuses on the integrated problem of long-term planning and short-term scheduling in a largescale refinery-petrochemical complex,and considers the overall manufacturing process from the upstream refinery to the downstream petrochemical *** time scales are incorporated from the planning and scheduling *** the end of each discrete time period,additional constraints are imposed to ensure material balance between different time *** time representation is applied to the planning subproblem,while continuous time is applied to the scheduling of ethylene cracking and polymerization processes in the petrochemical *** enterprise-wide mathematical model is formulated through mixed integer nonlinear *** solve the problem efficiently,a heuristic algorithm combined with a convolutional neural network(CNN),is *** variables are used as the CNN input,leading to the integration of a data-driven approach and classical optimization by which a heuristic algorithm is *** results do not only illustrate the detailed operations in a refinery and petrochemical complex under planning and scheduling,but also confirm the high efficiency of the proposed algorithm for solving large-scale problems.