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Recent advances in mathematical programming techniques for the optimization of process systems under uncertainty.
- Source :
-
Computers & Chemical Engineering . Aug2016, Vol. 91, p3-14. 12p. - Publication Year :
- 2016
-
Abstract
- Optimization under uncertainty has been an active area of research for many years. However, its application in Process Systems Engineering has faced a number of important barriers that have prevented its effective application. Barriers include availability of information on the uncertainty of the data (ad-hoc or historical), determination of the nature of the uncertainties (exogenous vs. endogenous), selection of an appropriate strategy for hedging against uncertainty (robust/chance constrained optimization vs. stochastic programming), large computational expense (often orders of magnitude larger than deterministic models), and difficulty of interpretation of the results by non-expert users. In this paper, we describe recent advances that have addressed some of these barriers for mostly linear models. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00981354
- Volume :
- 91
- Database :
- Academic Search Index
- Journal :
- Computers & Chemical Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 116159828
- Full Text :
- https://doi.org/10.1016/j.compchemeng.2016.03.002