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Tightening methods for continuous‐time mixed‐integer programming models for chemical production scheduling
Author(s) -
Merchan Andres F.,
Velez Sara,
Maravelias Christos T.
Publication year - 2013
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.14249
Subject(s) - scheduling (production processes) , integer programming , mathematical optimization , computer science , industrial engineering , process (computing) , production (economics) , operations research , mathematics , engineering , economics , operating system , macroeconomics
Significance Important advances in modeling chemical production scheduling problems have been made in recent years, yet effective solution methods are still required. We use an algorithm that uses process network and customer demand information to formulate powerful valid inequalities that substantially improve the solution process. In particular, we extend the ideas recently developed for discrete‐time formulations to continuous‐time models and show that these tightening methods lead to a significant decrease in computational time, up to more than three orders of magnitude for some instances. © 2013 American Institute of Chemical Engineers AIChE J , 59: 4461–4467, 2013