logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

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

delete2021-10-04
delete11
PRE
AI
I
Ilias Mitrai
P
Pródromos Daoutidis *
DOI：10.1021/acs.iecr.1c01570delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
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.
Keywords:
DYNAMIC OPTIMIZATION
LAGRANGEAN DECOMPOSITION
PROCESS OPERATIONS
INTEGRATION
MODEL
ALGORITHM
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

I
Industrial and Engineering Chemistry Research
IF:
3.9
Papers:
4.0W
Citations:
9.6W

Organization

No organization information available