Integrated scheduling and dynamic optimization for network batch processes

Yunfei Chu, Fengqi You*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


We address the integration of scheduling and dynamic optimization for batch processes that have complex network structures, allowing material splitting and mixing. The integrated problem is formulated into a mixed-integer nonlinear programming (MINLP) problem. To reduce the computational complexity, we develop a tailored and efficient decomposition method based on the framework of generalized Benders decomposition by exploiting the special structure of the integrated problem. The decomposed master problem is a scheduling problem with variable processing times and processing costs, as well as the Benders cuts. The primal problem comprises a set of separable dynamic optimization problems for the processing units. In comparison with the simultaneous method which solves the integrated problem by a general-purpose MINLP solver, the proposed method can reduce computational times by orders of magnitude, although global optimality of the solutions cannot be guaranteed for non-convex problems.

Original languageEnglish (US)
Pages (from-to)523-528
Number of pages6
JournalComputer Aided Chemical Engineering
StatePublished - Jan 1 2014


  • Dynamic optimization
  • Generalized Benders decomposition
  • Scheduling

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

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