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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
Author(s) -
Yadav Ranjana,
Malhotra AnnuVij,
Mishra Anuradha
Publication year - 2020
Publication title -
macromolecular theory and simulations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.37
H-Index - 56
eISSN - 1521-3919
pISSN - 1022-1344
DOI - 10.1002/mats.202000051
Subject(s) - data envelopment analysis , xyloglucan , copolymer , minimax , butyl acrylate , acrylate , mathematics , computer science , parametric statistics , linear programming , methyl acrylate , mathematical optimization , chemistry , biological system , organic chemistry , polysaccharide , statistics , polymer , biology
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.