An Efficient Scheduling Method for Crude Oil Operations in Refinery with Crude Oil Type Mixing Requirements

Nai Qi Wu, Li Ping Bai, Meng Chu Zhou

Research output: Contribution to journalArticlepeer-review

50 Scopus citations


With a combinatorial nature and hybrid characteristics, it is very challenging to schedule crude oil operations in a refinery and, up to now, there is no software tool for practical use in this field. To solve this problem, based on the two-level architecture in our previous work, for cases where crude oil mixing is required, this paper investigates the refining scheduling problem at the upper level. Based on the schedulability conditions, a three-stage approach is proposed. First, a linear programming model is developed to maximize productivity. Second, another linear programming model is built and solved to optimally obtain the mixed crude oil types and their amounts, and assign them into the distillers. Finally, this paper simply sequences and merges the oil parcels obtained at the second stage to form a desired schedule. Because the proposed approach mainly solves two linear programming problems, it is very efficient. An industrial case study is presented to illustrate the proposed approach.

Original languageEnglish (US)
Article number6872809
Pages (from-to)413-426
Number of pages14
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Issue number3
StatePublished - Mar 2016

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


  • Crude oil operations
  • linear programming
  • refinery process
  • short-term scheduling


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