J
Jianyong Sun
Researcher at Xi'an Jiaotong University
Publications - 103
Citations - 2814
Jianyong Sun is an academic researcher from Xi'an Jiaotong University. The author has contributed to research in topics: Evolutionary algorithm & Estimation of distribution algorithm. The author has an hindex of 19, co-authored 91 publications receiving 2227 citations. Previous affiliations of Jianyong Sun include Abertay University & University of Nottingham.
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Moea/d with adaptive weight adjustment
TL;DR: Experimental results indicate that MOEA/D-AWA outperforms the benchmark algorithms in terms of the IGD metric, particularly when the PF of the MOP is complex.
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DE/EDA: a new evolutionary algorithm for global optimization
TL;DR: Experimental results demonstrate that DE/EDA outperforms the DE algorithm and the EDA, and combines global information extracted by EDA with differential information obtained by DE to create promising solutions.
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Root gravitropism is regulated by a transient lateral auxin gradient controlled by a tipping-point mechanism
Leah R. Band,Darren M. Wells,Antoine Larrieu,Jianyong Sun,Alistair M. Middleton,Andrew P. French,Géraldine Brunoud,Ethel Mendocilla Sato,Michael Wilson,Benjamin Péret,Marina Oliva,Ranjan Swarup,Ilkka Sairanen,Geraint Parry,Karin Ljung,Tom Beeckman,Jonathan M. Garibaldi,Mark Estelle,Markus R. Owen,Kris Vissenberg,T. Charlie Hodgman,Tony P. Pridmore,John R. King,Teva Vernoux,Malcolm J. Bennett +24 more
TL;DR: This work used an Aux/IAA-based reporter, domain II (DII)-VENUS, in conjunction with a mathematical model to quantify auxin redistribution following a gravity stimulus and revealed that auxin is rapidly redistributed to the lower side of the root within minutes of a 90° gravity stimulus.
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An evolutionary algorithm with guided mutation for the maximum clique problem
TL;DR: An evolutionary algorithm with guided mutation (EA/G) for the maximum clique problem is proposed in this paper and experimental results show that EA/G outperforms the heuristic genetic algorithm of Marchiori and a MIMIC algorithm on DIMACS benchmark graphs.
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Parameter Estimation Using Metaheuristics in Systems Biology: A Comprehensive Review
TL;DR: This paper gives a comprehensive review of the application of metaheuristics to optimization problems in systems biology, mainly focusing on the parameter estimation problem (also called the inverse problem or model calibration).