On the development of novel chemicals using a systematic optimisation approach. Part II. Solvent design

Marcoulaki, Eftychia C.; Kokossis, Antonis

doi:10.1016/s0009-2509(99)00523-0

Cited by 98 publications

(58 citation statements)

References 23 publications

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“…Among the conventional optimization techniques, genetic algorithm (GA), simulated annealing (SA), and tabu search (TS) have their advantages. GA is a simulation of natural evolution and creates new better individuals by crossover, mutation, and selection; in this way, GA handles the linear and bound constraints and obtains fitter generations towards the optimazation objective.…”

Section: Introductionmentioning

confidence: 99%

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Development of CAMD based on the hybrid gene algorithm and simulated annealing algorithm and the application on solvent selection

Liu

Wen

Zhang³

2016

Can J Chem Eng

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In this paper, an evolutionary approach, improved CAMD based on the hybrid gene algorithm and simulated annealing algorithm (GASA), is developed. The new approach combines the feature of GA and SA, avoiding the problem of prematurity. With a new category strategy of candidate groups from the Mod UNIFAC group database adopted, a repair operator is introduced to guarantee the integrity of randomly generated molecules and thus the search of straight chain alkane as well as cyclane solutions can be performed together. The properties of molecules are obtained by the group contribution method. An example of extractive solvent selection for a methanol‐methyl acetate system has been illustrated in detail to further explain the method. The stability as well as other properties of the molecules which the authors think important is considered in the fitness function. Results of the example show that the fitness ranking values are better than those in the literature. The CAMD method in this paper can be used in practical chemical processes.

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Section: Introductionmentioning

confidence: 99%

“…Ourique first proposed the use of SA in CAMD. Kokossis et al employed SA to predict the molecular structure, successfully avoiding a combinatorial explosion. Wang and Achenie presented a hybrid global optimization approach that combines the outer approximation (OA) and SA algorithms for several solvent design problems.…”

Section: Introductionmentioning

confidence: 99%

Development of CAMD based on the hybrid gene algorithm and simulated annealing algorithm and the application on solvent selection

Liu

Wen

Zhang³

2016

Can J Chem Eng

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“…In comparison to previous decomposition approaches that relied on enumeration or stochastic optimization, 25,45 the use of deterministic optimization techniques at each stage of our approach leads to an efficient algorithm that is not limited by the number of solutions desired or the size of the molecule sought.…”

Section: Introductionmentioning

confidence: 99%

Optimization‐based framework for computer‐aided molecular design

Samudra

Sahinidis

2013

AIChE Journal

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A new framework to automate, augment, and accelerate steps in computer-aided molecular design is presented. The problem is tackled in three stages: (1) composition design, (2) structure determination, and (3) extended design. Composition identification and structure determination are decoupled to achieve computational efficiency. Using approximate group-contribution methods in the first stage, molecular compositions that fit design targets are identified. In the second stage, isomer structures of solution compositions are determined systematically, and structure-based property corrections are used to refine the solution pool. In the final stage, the design is extended beyond the scope of group-contribution methods by using problem-specific property models. At each design stage, novel optimization models and graph theoretic algorithms generate a large and diverse pool of candidates using an assortment of property models. The wide applicability and computational efficiency of the proposed methodology are illustrated through three case studies.

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“…This work has been applied to absorption processes and extended to dynamic models (Giovanoglou, Barlatier, Adjiman, Pistikopoulos & Cordiner, 2003). Another approach has been developed by Marcoulaki & Kokossis (2000), who have used a simulated annealing approach to integrate solvent and process design. Hostrup, Harper & Gani (1999) have proposed a hybrid method that combines heuristics and mathematical programming to develop an optimal owsheet and an optimal solvent.…”

Section: Introductionmentioning

confidence: 99%

Integrated solvent and process design using a SAFT-VR thermodynamic description: High-pressure separation of carbon dioxide and methane

Pereira¹,

Keskes²,

Galindo³

et al. 2011

Computers & Chemical Engineering

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On the development of novel chemicals using a systematic optimisation approach. Part II. Solvent design

Cited by 98 publications

References 23 publications

Development of CAMD based on the hybrid gene algorithm and simulated annealing algorithm and the application on solvent selection

Development of CAMD based on the hybrid gene algorithm and simulated annealing algorithm and the application on solvent selection

Optimization‐based framework for computer‐aided molecular design

Integrated solvent and process design using a SAFT-VR thermodynamic description: High-pressure separation of carbon dioxide and methane

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