Superstructure optimization

A process-synthesis problem can be formulated as a combination of tasks whose goal is the optimization of an economic objective function subject to constraints. Two types of mathematical techniques are the most used mixed-integer linear programming (MILP), and mixed-integer nonlinear programming (MINLP). 

Process synthesis by superstructure optimization consists of the identification of the best flowsheet from a superstructure that considers many possible alternatives, including the optimal one. A substantial advantage is that integration and design features may be considered simultaneously. At today s level of software technology the superstructure optimization is still an emerging technique. However, notable success has been achieved in numerous applications. The reference in this field is the book of Biegler et al. [6]. 

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Significant recent approaches to chemical reactor network synthesis can be classified into two categories, viz. superstructure optimization and network targeting. In the former, a superstructure is postulated and then an optimal sub-network within it is identified to maximize performance index (Kokossis and Floudas, 1990). 

Yeomans, H. and Grossmann, I.E. (1999) A systematic modeling framework of superstructure optimization in process synthesis. Computers el Chemical Engineering, 23, 709. 

There appears to be three fundamental approaches to the synthesis of chemical process flowsheets. The first, systematic generation, builds the flowsheet from smaller, more basic components strung together in such a way that raw materials eventually become transformed into the desired product. The second, evolutionary modification, starts with an existing flowsheet for the same or a similar product and then makes modifications as necessary to adopt the design to meet the objectives of the specific case at hand. The third, superstructure optimization, views synthesis as a mathematical optimization over structure this approach starts with a larger superflowsheet that contains embedded within it many redundant alternatives and interconnections and then systematically strips the less desirable parts of the superstructure away. 

The solution of significantly larger MINLP problems has been reported in the literature. For instance, Viswanathan and Grossmann (1990) reported the solution with DICOPT -E -E of the superstructure optimization of the HDA process (see Section VIII, Fig. 17) which involved 13 0-1 variables, 709 continuous variables, and 719 constraints. DICOPT-E -E obtained the solution in three major iterations requiring 482 seconds on an IBM-3090. Also, Viswanathan and Gross-... 

Maximization of throughput and minimization of desorbent consumption. e constraint method A superstructure optimization problem for SMB process is considered. An interior point optimizer (IPOPT) is used to solve the single objective subproblems. Kawajiri and Biegler (2006)... 

Ahmetovic, E. and Grossmann, I.E. (2011) Global superstructure optimization for the design of integrated process water networks. AIChE Journal, 57 (2), 434-457. 

Lee, S. Logsdon, J.S. Eoral, M.J. Grossmann. I.E. (2003) Superstructure optimization of the olefin separation process. ESCAPE-13 Proceedings, Lappeenranta, Finland. 

The olefin separation process involves handling a feed stream with a number of hydrocarbon components. The objective of this process is to separate each of these components at minimum cost. We consider a superstructure optimization for the olefin separation system that consists of several technologies for the separation task units and compressors, pumps, valves, heaters, coolers, heat exchangers. We model the major discrete decisions for the separation system as a generalized disjunctive programming (GDP) problem. The objective function is to minimize the annualized investment cost of the separation units and the utility cost. The GDP problem is reformulated as an MINLP problem, which is solved with the Outer Approximation (OA) algorithm that is available in DICOPT++/GAMS. The solution approach for the superstructure optimization is discussed and numerical results of an example are presented. 

Wang, B., Gebreslassie, B.H., You, R, 2013. Sustainable design and synthesis of hydrocarbon biorefinery via gasification pathway integrated life cycle assessment and technoeconomic analysis with multiobjective superstructure optimization. Comput. Chem. Eng. 52, 55-76. 

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