Optimal design of distillation systems with less than N− 1 columns for a class of four component mixtures

Cortez-González, J.; Segovia‐Hernández, Juan Gabriel; Hernández, Salvador; Gutiérrez‐Antonio, Claudia; Briones-Ramírez, Abel; Rong, Ben-Guang

doi:10.1016/j.cherd.2012.02.004

Cited by 5 publications

(4 citation statements)

References 39 publications

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“…Both of these shortages result in frequent optimization failure in the SM environment. To avoid the use of gradient information, a series of derivative-free optimization techniques, such as genetic algorithm, − simulated annealing, and particle swarm optimization, have been developed to optimize flowsheets based on the SM environment. But these kinds of optimization algorithms still have convergence problems.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Optimization of Complex Distillation Systems with a New Pseudo-transient Continuation Model

Luo

Yuan

2017

Ind. Eng. Chem. Res.

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Complex distillation systems, such as extractive distillation systems and thermally coupled distillation systems have important applications in chemical industry. However, simultaneous optimization of all the variables in these systems with the rigorous MESH model is still difficult because of both the convergence problem and integer optimization problem. In this work, based on the pseudo-transient continuation (PTC) approach, a simple and robust PTC distillation model was developed in the equation-oriented (EO) environment. It was based on the dynamic simulation but with a pseudo-hold-up correlation, which resulted in a well-posed and easily solved differential algebraic equation (DAE) system. Then, three optimization cases were studied to validate the performance of the bypass efficiency method and the new PTC model.

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Section: Introductionmentioning

confidence: 99%

Simultaneous Optimization of Complex Distillation Systems with a New Pseudo-transient Continuation Model

Luo

Yuan

2017

Ind. Eng. Chem. Res.

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“…The best and worst solutions obtained with BUMDA Algorithm are presented in Table II. They are compared with the best results reported by [37] using the same distillation train and same characteristics of the mixture. As it can be observed, the best design found by the BUMDA algorithm needs less total stage number while in terms of energy it requires approximately the same total heat duty.…”

Section: Discussion Of the Resultsmentioning

confidence: 97%

Constrained evolutionary optimization of a distillation train in chemical engineering

Gutiérrez-Guerra

Murrieta-Dueñas

Cortez-González

et al. 2013

2013 IEEE Congress on Evolutionary Computation

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Abstract-The optimal design and synthesis of distillation systems remains one of the most challenging problems in process engineering. The goal of this paper is to introduce an evolutionary approach for the optimization of the total energy consumption of distillation systems with constraints. Moreover, the contribution of this paper is a novel constraint handling technique that manages design goals as equality constraints, such as the purity and the recovery of the final components. In the literature of these problems prevail the use of inequality constraints; although easy to apply they may lead the search to suboptimal solutions. The case study is a distillation column sequence (DCS) for the separation of four components; this problem is easy to describe yet complex to solve so our approach can show its advantages. The evolutionary algorithm Boltzmann Univariate Marginal Distribution Algorithm, (BUMDA), performs the optimization. AspenONE c software is used for the rigorous evaluation of the fitness function of the population. The results show the efficacy performance of the proposed approach reaching near optimal designs in less than 3000 function evaluations.

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“…The same combination of process simulator and metaheuristic algorithm is adopted by Vazquez-Castillo et al (2009) to address the optimization of five distillation sequences. Subsequent works used a multiobjective GA ) for the optimization of thermally coupled distillation systems (Bravo-Bravo et al, 2010;Cortez-Gonzalez et al, 2012;Gutérrez-Antonio et al, 2011), and for the retrofit of a subcritical pulverized coal power plant with an MEA-based carbon capture and CO2 compression system (Eslick & Miller, 2011). Finally, Odjo et al (2011) also presented a general M a n u s c r i p t 5 framework for the synthesis of chemical processes using a hybrid approach with Hysys and genetic algorithms.…”

Section: Introductionmentioning

confidence: 99%

Integration of modular process simulators under the Generalized Disjunctive Programming framework for the structural flowsheet optimization

Navarro-Amorós

Ruiz‐Femenia

2014

Computers & Chemical Engineering

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HighlightsA new modeling framework that exploits the synergistic combination of commercial process simulators and GDP models Our methodology allows to include easily logical relationships among alternativesThe proposed tool uses a logic based Outer Approximation algorithmThe methodology is applied to the synthesis of a methanol plant where different alternatives AbstractThe optimization of chemical processes where the flowsheet topology is not kept fixed is a challenging discrete-continuous optimization problem. Usually, this task has been performed through equation based models. This approach presents several problems, as tedious and complicated component properties estimation or the handling of huge problems (with thousands of equations and variables). We propose a GDP approach as an alternative to the MINLP models coupled with a flowsheet program. The novelty of this approach relies on using a commercial modular process simulator where the superstructure is drawn directly on the graphical use interface of the simulator. This methodology takes advantage of modular process simulators (specially tailored numerical methods, reliability, and robustness) and the flexibility of the GDP formulation for the modeling and solution. The optimization tool proposed is successfully applied

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Optimal design of distillation systems with less than N− 1 columns for a class of four component mixtures

Cited by 5 publications

References 39 publications

Simultaneous Optimization of Complex Distillation Systems with a New Pseudo-transient Continuation Model

Simultaneous Optimization of Complex Distillation Systems with a New Pseudo-transient Continuation Model

Constrained evolutionary optimization of a distillation train in chemical engineering

Integration of modular process simulators under the Generalized Disjunctive Programming framework for the structural flowsheet optimization

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