Recent advances in mathematical programming techniques for the optimization of process systems under uncertainty

Ignacio E. Grossmann, Robert M. Apap, Bruno A. Calfa, Pablo García-Herreros, Qi Zhang
2016 Computers and Chemical Engineering  
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
more » ... 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.
doi:10.1016/j.compchemeng.2016.03.002 fatcat:kbdi23aghbh25dnd455t7atcdm