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Design of single‐product campaign batch plants under demand uncertainty
Author(s) -
Petkov Spas B.,
Maranas Costas D.
Publication year - 1998
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.690440415
Subject(s) - mathematical optimization , discretization , product (mathematics) , stochastic programming , production (economics) , lexicographical order , normality , integer (computer science) , nonlinear system , integer programming , representation (politics) , mode (computer interface) , computer science , mathematics , statistics , economics , mathematical analysis , physics , geometry , combinatorics , quantum mechanics , politics , political science , law , macroeconomics , programming language , operating system
A new method is introduced for optimally designing multiproduct batch plants under the single‐product campaign (SPC) production mode. Uncertain future product demands are described with normal probability distributions, and more than one processing unit of equal size are allowed per stage. A t the expense of imposing the normality assumption for product demand uncertainty and the SPC production mode, the original two‐stage stochastic optimization problem is transformed into a deterministic mixed‐integer nonlinear programming problem without relying on implicit or explicit discretization of the uncertain variables. This is accomplished through the explicit solution of the inner problem and the analytical integration overall product demand realizations. This problem representation and solution strategy result in savings of orders of magnitude over existing methods in computational requirements.