, Volume 139, Issue 1, pp 131162
First online:
Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications
 Christodoulos A. FloudasAffiliated withDepartment of Chemical Engineering, Princeton University Email author
 , Xiaoxia LinAffiliated withDepartment of Chemical Engineering, Princeton University
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This paper reviews the advances of mixedinteger linear programming (MILP) based approaches for the scheduling of chemical processing systems. We focus on the shortterm scheduling of general network represented processes. First, the various mathematical models that have been proposed in the literature are classified mainly based on the time representation. Discretetime and continuoustime models are presented along with their strengths and limitations. Several classes of approaches for improving the computational efficiency in the solution of MILP problems are discussed. Furthermore, a summary of computational experiences and applications is provided. The paper concludes with perspectives on future research directions for MILP based process scheduling technologies.
Keywords
chemical process scheduling mixedinteger linear programming (MILP) discretetime model continuoustime model branch and bound Title
 Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications
 Journal

Annals of Operations Research
Volume 139, Issue 1 , pp 131162
 Cover Date
 200510
 DOI
 10.1007/s104790053446x
 Print ISSN
 02545330
 Online ISSN
 15729338
 Publisher
 Kluwer Academic Publishers
 Additional Links
 Topics
 Keywords

 chemical process scheduling
 mixedinteger linear programming (MILP)
 discretetime model
 continuoustime model
 branch and bound
 Industry Sectors
 Authors

 Christodoulos A. Floudas ^{(1)}
 Xiaoxia Lin ^{(1)}
 Author Affiliations

 1. Department of Chemical Engineering, Princeton University, Princeton, NJ, 085445263, USA