Generalized Disjunctive Programming: A Framework for Formulation and Alternative Algorithms for MINLP Optimization

Grossmann, Ignacio E.; Ruiz, Juan Pablo Pizarro

doi:10.1007/978-1-4614-1927-3_4

Cited by 54 publications

(35 citation statements)

References 47 publications

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“…However, the subproblems in the initialization (Isub-LBOA), (Ifeas-LBOA), and in the main algorithm (sub-LBOA), (feas-LBOA) are smaller NLP problems than the ones in the nolninear OA, since they only contain a subset of the constants. Also, the logic based Outer Approximation sometimes requires fewer iterations of the master problem to converge [21].…”

Section: Terminate?mentioning

confidence: 99%

Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

Trespalacios

Grossmann

2014

Chemie Ingenieur Technik

151

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This work presents a review of the applications of mixed-integer nonlinear programming (MINLP) in process systems engineering (PSE). A review on the main deterministic MINLP solution methods is presented, including an overview of the main MINLP solvers. Generalized disjunctive programming (GDP) is an alternative higher-level representation of MINLP problems. This work reviews some methods for solving GDP models, and techniques for improving MINLP methods through GDP. The paper also provides a high-level review of the applications of MINLP in PSE, particularly in process synthesis, planning and scheduling, process control and molecular computing.

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Section: Terminate?mentioning

confidence: 99%

Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

Trespalacios

Grossmann

2014

Chemie Ingenieur Technik

151

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“…It can be solved by reformulating the disjunctions using a Big-M approach (Grossmann and Ruiz, 2012). Disjunctions are shown in Eq.(10).…”

Section: Distillation Sequences Nonsharp Separationsmentioning

confidence: 99%

Optimization of Chemical Processes Using Surrogate Models Based on a Kriging Interpolation

Quirante¹,

Javaloyes²,

Ruiz‐Femenia³

2015

Computer Aided Chemical Engineering

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Superstructure approaches are the solution to the difficult problem which involves the rigorous economic design of a distillation column. These methods require complex initialization procedures and they are hard to solve. For this reason, these methods have not been extensively used. In this work, we present a methodology for the rigorous optimization of chemical processes implemented on a commercial simulator using surrogate models based on a kriging interpolation.Several examples were studied, but in this paper, we perform the optimization of a superstructure for a non-sharp separation to show the efficiency and effectiveness of the method. Noteworthy that it is possible to get surrogate models accurate enough with up to seven degrees of freedom.

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“…Disjunctions (8) and (9) are transformed to MINLP constraints through standard techniques (Grossmann and Ruiz, 2012).…”

Section: Constraintsmentioning

confidence: 99%

Solution strategies to the stochastic design of mineral flotation plants

Jamett

Cisternas

Vielma

2015

Chemical Engineering Science

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The aim of this study is two-fold: first, to analyze the effect of stochastic uncertainty in the design of flotation circuits and second, to analyze different strategies for the solution of a two-stage stochastic problem applied to a copper flotation circuit. The paper begins by introducing a stochastic optimization problem whose aim is to find the best configuration of superstructure, equipment design and operational conditions, such as residence time and stream flows. Variability is considered in the copper price and ore grade. This variability is represented by scenarios with their respective probability of occurrence. The resulting optimization problem is a two-stage stochastic mixed integer nonlinear program (TS-MINLP), which can be extremely challenging to solve. For this reason, several solvers for this problem are compared and two stochastic programming methodologies are applied. The combination of these techniques allows the production of high quality solutions and an analysis of their sensitivity to epistemic uncertainty. The results show that the stochastic problem gives better designs because it allows operational parameters to adapt to the uncertainty of the parameters. The results also show that the flotation circuit structure can vary with the feed grade and copper price. The sensitivity analysis shows small to moderate variability with epistemically uncertain parameters.

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Generalized Disjunctive Programming: A Framework for Formulation and Alternative Algorithms for MINLP Optimization

Cited by 54 publications

References 47 publications

Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

Optimization of Chemical Processes Using Surrogate Models Based on a Kriging Interpolation

Solution strategies to the stochastic design of mineral flotation plants

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