Efficient Solution of Enterprise-Wide Optimization Problems Using Nested Stochastic Blockmodeling

Ilias Mitrai, Prodromos Daoutidis

Research output: Contribution to journalArticlepeer-review

Abstract

Enterprise-wide optimization seeks to improve the economic performance of process systems by considering simultaneously decisions at different time scales, resulting in large-scale optimization problems. In this paper, we propose the application of nested stochastic blockmodeling (nSBM) for the decomposition of such optimization problems. This approach allows the identification of the block structure of the problem at different hierarchical levels and the hierarchy itself. We consider problems of integration of scheduling and dynamic optimization and integration of planning, scheduling, and dynamic optimization for illustration. Application of nSBM reveals the multiscale nature of these optimization problems, and the exploitation of the structure of the problem at different hierarchical levels enables efficient solutions.

Original languageEnglish (US)
Pages (from-to)14476-14494
Number of pages19
JournalIndustrial and Engineering Chemistry Research
Volume60
Issue number40
DOIs
StatePublished - Oct 13 2021

Bibliographical note

Funding Information:
Financial support from NSF-CBET (Award Number 1926303) is gratefully acknowledged.

Publisher Copyright:
© 2021 American Chemical Society

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