Solution of chemical dynamic optimization systems using novel differential gradient evolution algorithm

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dc.authoridAkram, Sana/0000-0003-2038-9511
dc.authoridSaeed, Muhammad/0000-0002-7284-6908
dc.authoridFarman, Dr. Muhamamd/0000-0001-7616-0500
dc.contributor.authorTabassum, Muhammad Farhan
dc.contributor.authorSaeed, Muhammad
dc.contributor.authorAkgul, Ali
dc.contributor.authorFarman, Muhammad
dc.contributor.authorAkram, Sana
dc.date.accessioned2024-12-24T19:28:28Z
dc.date.available2024-12-24T19:28:28Z
dc.date.issued2021
dc.departmentSiirt Üniversitesi
dc.description.abstracttOptimization for all disciplines is essential and relevant. Optimization has played a vital role in industrial reactors' design and operation, separation processes, heat exchangers, and complete plants in Chemical Engineering. In this paper, a novel hybrid meta-heuristic optimization algorithm which is based on Differential Evolution (DE), Gradient Evolution (GE), and Jumping Technique (+) named Differential Gradient Evolution Plus (DGE+) is presented. The main concept of this hybrid algorithm is to enhance its exploration and exploitation ability. The proposed algorithm hybridizes the above-mentioned algorithms with the help of an improvised dynamic probability distribution, additionally provides a new shake off method to avoid premature convergence towards local minima. The performance of DGE+ is investigated in thirteen benchmark unconstraint functions, and the results are compared to the other state-of-the-art meta-heuristics. The comparison shows that the proposed algorithm can outperform the other state-of-the-art meta-heuristics in almost all benchmark functions. To evaluate the precision and robustness of the DGE+ it has also been applied to complex chemical dynamic optimization systems such as optimization of a multimodal continuous stirred tank reactor, Lee-Ramirez bioreactor, Six-plate gas absorption tower, and optimal operation of alkylation unit, the results of comparison revealed that the proposed algorithm can provide very compact, competitive and promising performance overall complex non-linear chemical design problems.
dc.identifier.doi10.1088/1402-4896/abd440
dc.identifier.issn0031-8949
dc.identifier.issn1402-4896
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85099258605
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1088/1402-4896/abd440
dc.identifier.urihttps://hdl.handle.net/20.500.12604/7074
dc.identifier.volume96
dc.identifier.wosWOS:000605842400001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIop Publishing Ltd
dc.relation.ispartofPhysica Scripta
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.subjectmeta-heuristics
dc.subjecthybridization
dc.subjectdifferential evolution
dc.subjectgradient evolution
dc.subjectconstrained optimization
dc.subjectbenchmark test functions
dc.subjectchemical engineering design problems
dc.titleSolution of chemical dynamic optimization systems using novel differential gradient evolution algorithm
dc.typeArticle

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