Data Envelopment Analysis and Decision Maker Models: An Innovative Approach for Optimization of Reaction Variables of Graft Copolymerization of Poly(butyl acrylate) to Tamarind Seed Xyloglucan,Macromolecular Theory and Simulations

当前位置： X-MOL 学术 › Macromol. Theor. Simul. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Data Envelopment Analysis and Decision Maker Models: An Innovative Approach for Optimization of Reaction Variables of Graft Copolymerization of Poly(butyl acrylate) to Tamarind Seed Xyloglucan
Macromolecular Theory and Simulations ( IF 1.8 ) Pub Date : 2020-09-02 , DOI: 10.1002/mats.202000051
Ranjana Yadav ₁ , AnnuVij Malhotra ₂ , Anuradha Mishra ₁

Affiliation

This article presents a novel methodology using a combination of non‐parametric frontier analysis models, data envelopment analysis (DEA), and decision maker (DM) model to optimize real‐time reaction variables, that is, concentration of butyl acrylate, time duration of the reaction, and temperature for precision synthesis of poly(butyl acrylate) (PBA) and xyloglucan (tamarind seed polysaccharide) graft copolymers.The copolymer samples (units) obtained by a different set of reaction variables and conditions are ranked using DEA to identify the efficient units. An appropriate minimum weight restriction is imposed by the DM on the chosen inputs and output by linear programming models that are designed in such a way that each DEA efficient unit can get “maximin” weight. The model predictions for reaction parameters and experimental data obtained are found to be very close to each other.

中文翻译：

数据包络分析和决策者模型：优化丙烯酸丁酯与罗望子种子木葡聚糖接枝共聚反应变量的创新方法

本文提出了一种新颖的方法，结合了非参数前沿分析模型，数据包络分析（DEA）和决策者（DM）模型来优化实时反应变量，即丙烯酸丁酯的浓度，反应时间精密合成聚丙烯酸丁酯（PBA）和木葡聚糖（罗望子种子多糖）接枝共聚物的反应和温度。使用DEA对通过不同反应变量和条件获得的共聚物样品（单元）进行分级，以识别有效单位。DM通过线性编程模型对所选的输入和输出施加适当的最小重量限制，该线性编程模型的设计方式是使每个DEA有效单元都能获得“最大”重量。

更新日期：2020-09-02

点击分享查看原文

点击收藏

阅读更多本刊最新论文本刊介绍/投稿指南11