Multi‐Objective Optimization of Semi‐Batch Copolymerization Reactors Using Adaptations of Genetic Algorithm

Summary: The polymerization of styrene‐acrylonitrile (SAN) random copolymers in semi‐batch reactors is optimized using multiple objective functions that are often conflicting and non‐commensurate in nature. These include the average composition of the copolymer product, its number‐average molecular weight, its polydispersity index, and the conversion of monomers attained in the reactor. Two decision/control variables are used, namely, the rate of continuous addition of a monomer‐solvent‐initiator mixture (having a specified and fixed composition) and the history of the temperature in the reactor. The elitist non‐dominated sorting genetic algorithm, NSGA‐II, is adapted and used for decision variables that are functions of time (trajectory optimization). This robust, AI (artificial intelligence)‐based technique, enables the solution of far more complex optimization problems than those reported in the literature. A set of several non‐dominating (equally good) Pareto optimal solutions was obtained. These provide insights into the conflicting nature of the objective functions. An engineer (decision maker) can then use his judgment (often intuitive) to choose the preferred solution from among these possibilities.

Pareto set of optimal solutions and some corresponding state variables for a Reference Problem.     

New analysis of the optimization of electromagnetic shielding properties using conducting polymers and a multi‐objective approach

Recently, an approach was proposed to optimize multi‐layer shields of polyaniline–polyurethane (PAni/PU) conducting composites in the microwave band. Though by this method shields for different applications can be obtained which are light‐weight and offer a low percolation threshold, the full potential of the design process could not be tapped since the underlying optimization problem includes only one objective. In this work we go one step beyond and re‐formulate the design problem as a multi‐objective optimization problem (MOP). To be more precise, we involve simultaneously the shielding efficiency as well as the weight and the cost of the material—i.e. all the requirements for modern shielding materials—within the optimization process. After having stated the model we present two possible ways to approximate the solution set—the so‐called Pareto set—and address the related and important decision‐making problem. All steps are demonstrated on a particular three‐layered composite in order to show the applicability of the novel approach. Copyright © 2008 John Wiley & Sons, Ltd.     

Multi‐Objective Optimization of a Batch Copoly(ethylene‐polyoxyethylene terephthalate) Reactor Using Different Adaptations of Nondominated Sorting Genetic Algorithm

Summary: A multi‐objective optimization is carried out for a copoly(ethylene‐polyoxyethylene terephthalate) (CEPT) batch reactor using different adaptations of the elitist nondominated sorting genetic algorithm (NSGA‐II). Several two objective function problems are formulated and solved. One objective is to minimize the total copolymerization time and other objective is to minimize the formation of total undesirable side products, namely, acid end group, vinyl ester end group, diethylene glycol ester end group of polyethylene terephthalate, and diethylene glycol. End‐point constraint is incorporated to obtain the specified number‐average degree of copolymerization. The operating temperature history of batch CEPT reactor is the only important decision variable for first optimization problem, whereas operating temperature history and molar ratio of feed to the reactor are taken as decision variables for the second optimization problem. Optimal Pareto frontiers are obtained for both the problems studied. In order to operate the polymerization reactor optimally, it is found that higher isothermal temperature history is needed for short copolymerization time, whereas lower nonisothermal temperature history is required for higher copolymerization time. The results of NSGA‐II technique are analyzed and compared with the jumping gene (JG) and adapted jumping gene (aJG) operator in NSGA‐II separately. It is found that NSGA‐II‐JG is superior to NSGA‐II and NSGA‐II‐aJG.

Optimization of a batch copoly(ethylene‐polyoxyethylene terephthalate) reactor.     

Structure‐based ligand design by a build‐up approach and genetic algorithm search in conformational space

Program to engineer peptides (PEP) is a build‐up approach for ligand docking and design with implicit solvation. It requires the knowledge of a seed from which it iteratively grows polymeric ligands consisting of any type of amino acid, i.e., natural and/or nonnatural from a user‐defined library. At every growing step, a genetic algorithm is used for conformational optimization of the last added monomer in the rigid binding site. Pruning is performed at every growing step by selecting sequences according to binding energy with electrostatic solvation. PEP is applied to three members of the caspase family of cysteine proteases using Asp at P₁ as seed. The optimal P₄–P₂ peptide recognition motifs and variants thereof are docked correctly in the active site (backbone root‐mean‐square deviation < 0.9 Å). Moreover, for each caspase, the P₄–P₂ sequences of potent aldehyde inhibitors are ranked among the 15 hits with the most favorable PEP energy. © 2001 John Wiley & Sons, Inc. J Comput Chem 22: 1956–1970, 2001     

Multi‐criteria optimization for ultrasonic‐assisted extraction of antioxidants from Pericarpium Citri Reticulatae using response surface methodology,an activity‐based approach

An activity‐based approach to optimize the ultrasonic‐assisted extraction of antioxidants from Pericarpium Citri Reticulatae (Chenpi in Chinese) was developed. Response surface optimization based on a quantitative composition‐activity relationship model showed the relationships among product chemical composition, antioxidant activity of extract, and parameters of extraction process. Three parameters of ultrasonic‐assisted extraction, including the ethanol/water ratio, Chenpi amount, and alkaline amount, were investigated to give optimum extraction conditions for antioxidants of Chenpi: ethanol/water 70:30 v/v, Chenpi amount of 10 g, and alkaline amount of 28 mg. The experimental antioxidant yield under the optimum conditions was found to be 196.5 mg/g Chenpi, and the antioxidant activity was 2023.8 μmol Trolox equivalents/g of the Chenpi powder. The results agreed well with the second‐order polynomial regression model. This presented approach promised great application potentials in both food and pharmaceutical industries.     

Zinc oxide nanorod‐loaded activated carbon for ultrasound‐assisted adsorption of safranin O: Central composite design and genetic algorithm optimization

This paper focuses on the development of an effective methodology to obtain the optimum ultrasonic‐assisted removal of a dye, safranin O (SO), under optimum conditions that maximize the removal percentage, using ZnO nanorod‐loaded activated carbon (ZnO‐NRs‐AC) in aqueous solution. Central composite design coupled with genetic algorithm was used for parameter optimization. The effects of variables such as pH, initial dye concentration, mass of ZnO‐NRs‐AC and sonication time were studied. The interactive and main effects of these variables were evaluated using analysis of variance. The structural and physicochemical properties of the ZnO‐NRs‐AC adsorbent were investigated using field emission scanning electron microscopy and X‐ray diffraction. Adsorption equilibrium data were fitted well with the Langmuir isotherm and the maximum monolayer capacity was found to be 32.06 mg g^?1. Studies of the adsorption kinetics of the SO dye showed a rapid sorption dynamic with a ^pseudo‐second‐order kinetic model, suggesting a chemisorption mechanism.     

Development of multi‐response optimization and quadratic calibration curve for determination of ten pesticides in complex sample matrices using QuEChERS dispersive liquid–liquid microextraction followed by gas chromatography

In this study, QuEChERS combined with dispersive liquid‐liquid microextraction is developed for extraction of ten pesticides in complex sample matrices of water and milk. In this regard, effective factors of proposed extraction technique combined with gas chromatography with flame ionization detector were designed, modeled, and optimized using central composite design, multiple linear regression, and Nelder–Mead simplex optimization. Later, univariate calibration model for ten pesticides was developed in concentration range of 0.5–100 ng/mL. Surprisingly, quadratic calibration behavior was observed for some of the pesticides. In this regard, Mandel's test was used for evaluating linearity and types of calibration equation. Finally, four pesticides followed linear calibration curve with sensitivity (0.23–0.66 mL/ng), analytical sensitivity (0.20–0.32), regression coefficient (0.988–0.995), limit of detection (0.39–1.83 ng/mL), and limit of quantitation (1.30–6.10 ng/mL) and six of them followed quadratic calibration curve with sensitivity (0.18–0.93 mL/ng), analytical sensitivity (0.25–0.86), regression coefficient (0.944–0.999), limit of detection (0.59–1.92 ng/mL), and limit of quantitation (1.96–6.40 ng/mL). The calculated limits of detection were below the maximum residue limits according to European Union pesticides database of European Commission. Finally, the proposed analytical method was used for determination of ten pesticides in water and milk samples.     

LLE for the extraction of alcohol from aqueous solutions with diethyl ether and dichloromethane at 293.15 K, parameter estimation using a hybrid genetic based approach

Experimental liquid-liquid equilibrium (LLE) data for the extraction of methanol, ethanol and 1-propanol from water by diethyl ether and dichloromethane at 293.15 K and at ambient pressure were investigated. Data for the binodal curves have been determined by cloud-point titration method and conjugate points on tie-line were obtained by correlating the refractive index of the binodal curves as a function of composition. The experimental ternary (liquid + liquid) equilibrium data have been estimated using the NRTL and UNIQUAC activity coefficient models to obtain the binary interaction parameters of these components by a combination of Levenberg-Marquardt method and the genetic algorithm based method. The distribution coefficients and the selectivity factor of the solvent used were calculated and presented. From our experimental and calculated results, we conclude that for the extraction of alcohol from aqueous solutions with dichloromethane solvent has a higher selectivity factor than the diethyl ether solvent.     

基于遗传算法优化的约束背景双线性分解算法用于改进高效液相色谱灰色分析体系的校正结果

该文采用约束背景双线性分解算法(CBBL)对以高效液相色谱(HPLC)方法分离分析的灰色分析体系进行了多元校正研究。针对采用包括CBBL在内的矩阵校正方法处理HPLC灰色分析体系的固有缺陷,即在相关组分的色谱保留时间重现性较低的情形下多元校正的结果不理想,对CBBL方法进行了改进,即将待测组分的浓度与组分的色谱保留时间同时作为优化的参量引入CBBL,并采用遗传算法(GA)优化CBBL,对于模拟的组分保留时间飘移严重的HPLC灰色分析体系及保留时间重现性不佳的多种酚类化合物组成的实际HPLC灰色分析体系进行了多元校正分析,成功克服了经典CBBL的固有缺陷,取得了较理想的多元校正结果。另外,该研究所建议的方法的校正结果也显著优于传统的残差双线性分解法(RBL)以及秩消失因子分析法(RAFA)。     

SMPBS: Web server for computing biomolecular electrostatics using finite element solvers of size modified Poisson‐Boltzmann equation

SMPBS (Size Modified Poisson‐Boltzmann Solvers) is a web server for computing biomolecular electrostatics using finite element solvers of the size modified Poisson‐Boltzmann equation (SMPBE). SMPBE not only reflects ionic size effects but also includes the classic Poisson‐Boltzmann equation (PBE) as a special case. Thus, its web server is expected to have a broader range of applications than a PBE web server. SMPBS is designed with a dynamic, mobile‐friendly user interface, and features easily accessible help text, asynchronous data submission, and an interactive, hardware‐accelerated molecular visualization viewer based on the 3Dmol.js library. In particular, the viewer allows computed electrostatics to be directly mapped onto an irregular triangular mesh of a molecular surface. Due to this functionality and the fast SMPBE finite element solvers, the web server is very efficient in the calculation and visualization of electrostatics. In addition, SMPBE is reconstructed using a new objective electrostatic free energy, clearly showing that the electrostatics and ionic concentrations predicted by SMPBE are optimal in the sense of minimizing the objective electrostatic free energy. SMPBS is available at the URL: smpbs.math.uwm.edu © 2017 Wiley Periodicals, Inc.