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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/18967
Title: Application of Laplacian Biogeography-Based optimization: Optimal extraction of bioactive compounds from Ashwgandha
Authors: Garg V.
Deep K.
Deep K.
Das K.N.
Bansal J.C.
Pant M.
Nagar A.
Published in: Proceedings of Advances in Intelligent Systems and Computing
Abstract: In this paper, the problem of extraction of bioactive compounds from the plant Ashwagandha is formulated as a nonlinear unconstrained optimization problem with more than one objective. Further this problem is solved using Laplacian Biogeography-Based Optimization. This paper focuses on the maximum extraction of two bioactive compounds (withaferin A and withanolide-A) from the roots of Ashwgandha (Withania somnifera). There are two objective functions each representing the maximizing of two bioactive compounds, i.e., withaferin A and withanolide A. The output of the yields is dependent on two factors namely, concentration of methanol and extraction temperature. This nonlinear optimization problem is converted into single objective problem using weighted sum approach and then solved using Laplacian Biogeography-Based Optimization (LX-BBO). Comparing these results with the previously reported results, it can be concluded that LX-BBO works comparatively well for these kind of optimization problems. © Springer Science+Business Media Singapore 2016.
Citation: Proceedings of Advances in Intelligent Systems and Computing, (2016), 805- 812
URI: https://doi.org/10.1007/978-981-10-0451-3_72
http://repository.iitr.ac.in/handle/123456789/18967
Issue Date: 2016
Publisher: Springer Verlag
Keywords: Biogeography-Based Optimization
Extraction of compounds
Laplacian BBO
Real coded Genetic Algorithm
Ecology
Extraction
Genetic algorithms
Heuristic algorithms
Laplace transforms
Nonlinear programming
Optimization
Soft computing
Biogeography-based optimizations
Extraction temperatures
Laplacians
Non-linear optimization problems
Optimization problems
Real coded genetic algorithm
Unconstrained optimization problems
Weighted sum approaches
Problem solving
ISBN: 9790000000000
ISSN: 21945357
Author Scopus IDs: 56594391300
8561208900
Author Affiliations: Garg, V., Department of Mathematics, Indian Institute of Technology, Roorkee, India
Deep, K., Department of Mathematics, Indian Institute of Technology, Roorkee, India
Corresponding Author: Garg, V.; Department of Mathematics, Indian Institute of TechnologyIndia; email: vanitagarg16@gmail.com
Appears in Collections:Conference Publications [MA]

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