Centralized-decentralized optimization for refinery scheduling

Nikisha Shah, Georgios K.D. Saharidis, Zhenya Jia, Marianthi G. Ierapetritou

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


This paper presents a novel decomposition strategy for solving large scale refinery scheduling problems. Instead of formulating one huge and unsolvable MILP or MINLP for centralized problem, we propose a general decomposition scheme that generates smaller sub-systems that can be solved to global optimality. The original problem is decomposed at intermediate storage tanks such that inlet and outlet streams of the tank belong to the different sub-systems. Following the decomposition, each decentralized problem is solved to optimality and the solution to the original problem is obtained by integrating the optimal schedule of each sub-systems. Different case studies of refinery scheduling are presented to illustrate the applicability and effectiveness of the proposed decentralized strategy. The conditions under which these two types of optimization strategies (centralized and decentralized) give the same optimal result are discussed.

Original languageEnglish (US)
Pages (from-to)2091-2105
Number of pages15
JournalComputers and Chemical Engineering
Issue number12
StatePublished - Dec 10 2009

All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)
  • Computer Science Applications


  • Centralized
  • Decentralized
  • Optimization
  • Refinery
  • Scheduling


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