Tightening methods for continuous-time mixed-integer programming models for chemical production scheduling

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 substanti...

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Bibliographic Details
Published inAIChE journal Vol. 59; no. 12; pp. 4461 - 4467
Main Authors Merchan, Andres F., Velez, Sara, Maravelias, Christos T.
Format Journal Article
LanguageEnglish
Published New York Blackwell Publishing Ltd 01.12.2013
American Institute of Chemical Engineers
Subjects
Algorithms
demand propagation
Integer programming
Mixed-integer programming
Production scheduling
valid inequalities
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ISSN0001-1541
1547-5905
DOI10.1002/aic.14249

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Summary: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
Bibliography:istex:F02C46820E4AAC86F7B57B2968F0E26194A95C1A
ark:/67375/WNG-J6JJW0HW-6
National Science Foundation - No. CBET-1066206
ArticleID:AIC14249
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0001-1541
1547-5905
DOI:10.1002/aic.14249