GHANSHYAM G. TEJANI

Dr. GHANSHYAM G. TEJANI

Industrial Engineering and Management, Yuan Ze University, Taoyuan District, Taoyuan, Taiwan
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2018 in Knowledge-Based Systems
Verified
Journal Article
Closed access
GHANSHYAM G. TEJANIGHANSHYAM G. TEJANI
GHANSHYAM G. TEJANI
VSVimal J. Savsani
Vimal J. Savsani
VPVivek Patel
Vivek Patel
Seyedali MirjaliliSeyedali Mirjalili
Seyedali Mirjalili

18 April 2021 in Archives of Computational Methods in Engineering
Verified
Journal Article
Closed access
PDF file
TKTawatchai Kunakote
Tawatchai Kunakote
NSNumchoak Sabangban
Numchoak Sabangban
SKSumit Kumar
Sumit Kumar
GHANSHYAM G. TEJANIGHANSHYAM G. TEJANI
GHANSHYAM G. TEJANI
Natee PanagantNatee Panagant
Natee Panagant
AYAli Rıza Yıldız
Ali Rıza Yıldız

1 July 2019 in Expert Systems with Applications
Verified
Journal Article
Closed access
GHANSHYAM G. TEJANIGHANSHYAM G. TEJANI
GHANSHYAM G. TEJANI
NPNantiwat Pholdee
Nantiwat Pholdee
Sujin BureeratSujin Bureerat
Sujin Bureerat
DPDoddy Prayogo
Doddy Prayogo
Amir H GandomiAmir H Gandomi
Amir H Gandomi

21 February 2016 in Journal of Computational Design and Engineering
Verified
Journal Article
Open access
GHANSHYAM G. TEJANIGHANSHYAM G. TEJANI
GHANSHYAM G. TEJANI
VSVimal J. Savsani
Vimal J. Savsani
VPVivek Patel
Vivek Patel
The symbiotic organisms search (SOS) algorithm is an effective metaheuristic developed in 2014, which mimics the symbiotic relationship among the living beings, such as mutualism, commensalism, and parasitism, to survive in the ecosystem. In this study, three modified versions of the SOS algorithm are proposed by introducing adaptive benefit factors in the basic SOS algorithm to improve its efficiency. The basic SOS algorithm only considers benefit factors, whereas the proposed variants of the SOS algorithm, consider effective combinations of adaptive benefit factors and benefit factors to study their competence to lay down a good balance between exploration and exploitation of the search space. The proposed algorithms are tested to suit its applications to the engineering structures subjected to dynamic excitation, which may lead to undesirable vibrations. Structure optimization problems become more challenging if the shape and size variables are taken into account along with the frequency. To check the feasibility and effectiveness of the proposed algorithms, six different planar and space trusses are subjected to experimental analysis. The results obtained using the proposed methods are compared with those obtained using other optimization methods well established in the literature. The results reveal that the adaptive SOS algorithm is more reliable and efficient than the basic SOS algorithm and other state-of-the-art algorithms. Highlights Correlation between organisms, optimization and engineering. Adaptive symbiotic organisms search (SOS) algorithm is proposed. Implementation on structural design problems. Effective over other methods.

1 April 2023 in Knowledge-Based Systems
Verified
Journal Article
Closed access
SKSumit Kumar
Sumit Kumar
Natee PanagantNatee Panagant
Natee Panagant
GHANSHYAM G. TEJANIGHANSHYAM G. TEJANI
GHANSHYAM G. TEJANI
NPNantiwat Pholdee
Nantiwat Pholdee
Sujin BureeratSujin Bureerat
Sujin Bureerat
PPPinank Patel
Pinank Patel

1 December 2018 in Knowledge-Based Systems
Verified
Journal Article
Closed access
GHANSHYAM G. TEJANIGHANSHYAM G. TEJANI
GHANSHYAM G. TEJANI
NPNantiwat Pholdee
Nantiwat Pholdee
Sujin BureeratSujin Bureerat
Sujin Bureerat
DPDoddy Prayogo
Doddy Prayogo