Design and Optimization of Pressure Swing Distillation using a Stochastic Algorithm based in the Boltzmann Distribution

Cortez-González, J.; Murrieta-Dueñas, Rodolfo; Gutiérrez-Guerra, Roberto; Segovia‐Hernández, Juan Gabriel; Hernández-Aguirre, Arturo

doi:10.1016/b978-0-444-59519-5.50138-6

Cited by 2 publications

(2 citation statements)

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“…However, recently an algorithm called the Boltzmann univariate marginal distribution algorithm (BUMDA) was developed . This algorithm has demonstrated great efficacy and robustness for optimizing considerably complex problems in chemical engineering …”

Section: Optimization Toolsmentioning

confidence: 99%

“…44 This algorithm has demonstrated great efficacy and robustness for optimizing considerably complex problems in chemical engineering. 45 In this work, the Pareto set can be described in terms of the total annual cost (TAC), energy consumption in the reboiler, and carbon dioxide emissions. This comparison is proposed in order to determine simultaneously the most suitable balance between the total annual cost, energy consumption, and carbon dioxide emissions.…”

Section: Optimization Toolsmentioning

confidence: 99%

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Design and Optimization of Heat-Integrated Distillation Column Schemes through a New Robust Methodology Coupled with a Boltzmann-Based Estimation of Distribution Algorithm

Gutiérrez-Guerra

Cortez-González

Murrieta-Dueñas

et al. 2014

Ind. Eng. Chem. Res.

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ABSTRACT:The technology of the heat-integrated distillation column (HIDiC) has shown to be a potential energy-saving alternative for separating close-boiling mixtures. However, the economic aspects are a critical factor to extensive use of this distillation sequence in real applications. In this research, a novel stochastic optimization algorithm called Boltzmann univariate marginal distribution algorithm (BUMDA) with constraints handling has been implemented to optimize HIDiC sequences. Three binary mixtures were examined: butanol−isobutanol, n-heptane−cyclohexane, and benzene−toluene. The evaluation was performed by applying a new robust methodology using the interface Matlab−Excel−Aspen Plus. The model Radfrac was used in the simulations in Aspen Plus. The minimization of the total annual cost was established as the fitness function of the problem. Results showed the great robustness presented by the BUMDA algorithm for solving successfully this kind of complex optimization problem. Thus, the HIDiC design to separate the alcohol mixture showed energy savings of 84% and a cost that was lower (2%) than that of the conventional column. In addition, the hydrocarbon mixtures reached energy savings of 62.5% (nheptane−cyclohexane) and 52.5% (benzene−toluene). Nevertheless, the total annual cost (TAC) of the HIDiC is larger than the TAC of the conventional column (32% and 35%, respectively).

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Section: Optimization Toolsmentioning

confidence: 99%

Section: Optimization Toolsmentioning

confidence: 99%