Efficient decomposition method for integrating production sequencing and dynamic optimization for a Multi-Product CSTR

Yunfei Chu, Fengqi You*

*Corresponding author for this work

Research output: Contribution to journalConference article

Abstract

Integration of scheduling and control can improve the overall performance of a manufacturing process. However, the integration leads to a mixed-integer dynamic optimization problem (MIDO), which could be challenging to solve. We propose a novel algorithm based on the generalized Bender decomposition method that takes advantage of the special structure of the integrated problem. It decomposes the binary variables from the dynamic optimization. The resulting master problem is a mixed integer linear program (MILP) while the primal problem is a coupled dynamic optimization. Compared with the conventional simultaneous method, the proposed decomposition algorithm can reduce the computational time by over one order of magnitude in a case study.

Original languageEnglish (US)
Pages (from-to)715-720
Number of pages6
JournalChemical Engineering Transactions
Volume39
Issue numberSpecial Issue
DOIs
StatePublished - Jan 1 2014
Event17th Conference on Process Integration, Modelling and Optimisation for Energy Saving and Pollution Reduction, PRES 2014 - Prague, Czech Republic
Duration: Aug 23 2014Aug 27 2014

ASJC Scopus subject areas

  • Chemical Engineering(all)

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