Tinkle Chugh

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Yaochu JinA. v. Humboldt Professor for AI, Bielefeld University, Germany; University of Surrey, UKVerified email at uni-bielefeld.de
Karthik SindhyaSolita OyVerified email at solita.fi
Jussi HakanenSenior AI Scientist, Silo AIVerified email at silo.ai
Handing WangSchool of Artificial Intelligence, Xidian UniversityVerified email at xidian.edu.cn
Alma RahatSenior Lecturer in Data Science, Swansea UniversityVerified email at swansea.ac.uk
Richard AllmendingerProfessor at The University of Manchester, UK, Fellow of the Alan Turing InstituteVerified email at manchester.ac.uk
Jonathan FieldsendProfessor of Computational Intelligence, Department of Computer Science, University of ExeterVerified email at exeter.ac.uk
Nirupam ChakrabortiVisiting Professor Czech Technical University, Prague. Former Professor IIT, IndiaVerified email at fs.cvut.cz
Atanu MazumdarPostdoctoral ResearcherVerified email at aalto.fi
Dr Hemant Kumar SinghSenior Lecturer, University of New South Wales, Canberra, AustraliaVerified email at adfa.edu.au
Professor Tapabrata RayUniversity of New South Wales, CanberraVerified email at adfa.edu.au
Manuel López-IbáñezAlliance Manchester Business School, University of Manchester, UKVerified email at manchester.ac.uk
Pramudita Satria PalarAssistant Professor, Mechanical and Aerospace Engineering (Institut Teknologi Bandung)Verified email at ftmd.itb.ac.id
Kishalay MitraProfessor, Indian Institute of Technology HyderabadVerified email at iith.ac.in
Saptarshi MajumdarProfessor, Indian Institute of Technology, Hyderabad, IndiaVerified email at che.iith.ac.in
Anitha MogilicharlaChaitanya Bharathi Institute of TechnologyVerified email at cbit.ac.in
Vesa OjalehtoVerified email at jyu.fi
Chaoli SunSchool of Computer Science and Technology, Taiyuan University of Science and TechnologyVerified email at tyust.edu.cn
Martin ZaeffererTH Köln University of Applied SciencesVerified email at th-koeln.de
Vanessa Volzmodl.aiVerified email at modl.ai

Tinkle Chugh

Lecturer (Assistant Professor) in Computer Science, University of Exeter

Verified email at exeter.ac.uk - Homepage

Evolutionary computation multi-objective optimization machine learning decision making Bayesian optimisation


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A surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive many-objective optimization T Chugh, Y Jin, K Miettinen, J Hakanen, K Sindhya IEEE Transactions on Evolutionary Computation 22 (1), 129-142, 2016	335	2016
Data-driven evolutionary optimization: An overview and case studies Y Jin, H Wang, T Chugh, D Guo, K Miettinen IEEE Transactions on Evolutionary Computation 23 (3), 442-458, 2018	320	2018
Handling computationally expensive multiobjective optimization problems with evolutionary algorithms : A survey T Chugh, K Sindhya, J Hakanen, K Miettinen https://jyu.finna.fi/Record/jykdok.1506554, 2015	210*	2015
A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem T Chugh, N Chakraborti, K Sindhya, Y Jin Materials and Manufacturing Processes 32 (10), 1172-1178, 2017	95	2017
A multiple surrogate assisted decomposition-based evolutionary algorithm for expensive multi/many-objective optimization A Habib, HK Singh, T Chugh, T Ray, K Miettinen IEEE Transactions on Evolutionary Computation 23 (6), 1000-1014, 2019	74	2019
Surrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system T Chugh, K Sindhya, K Miettinen, Y Jin, T Kratky, P Makkonen 2017 IEEE Congress on Evolutionary Computation (CEC), 1541-1548, 2017	37	2017
Connections of reference vectors and different types of preference information in interactive multiobjective evolutionary algorithms J Hakanen, T Chugh, K Sindhya, Y Jin, K Miettinen 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2016	29	2016
On constraint handling in surrogate-assisted evolutionary many-objective optimization T Chugh, K Sindhya, K Miettinen, J Hakanen, Y Jin Parallel Problem Solving from Nature–PPSN XIV: 14th International Conference …, 2016	28	2016
Multi-Objective Optimization of Bulk Vinyl Acetate Polymerization with Branching KM Anitha Mogilicharla, Tinkle Chugh, Saptarshi Materials and Manufacturing Processes 29 (2), 210-217, 2014	27	2014
An interactive simple indicator-based evolutionary algorithm (I-SIBEA) for multiobjective optimization problems T Chugh, K Sindhya, J Hakanen, K Miettinen 8th International conference on Evolutionary Multi-Criteria Optimization, 2015	26	2015
A feature rich distance-based many-objective visualisable test problem generator JE Fieldsend, T Chugh, R Allmendinger, K Miettinen Proceedings of the Genetic and Evolutionary Computation Conference, 541-549, 2019	24	2019
Surrogate-assisted evolutionary optimization of large problems T Chugh, C Sun, H Wang, Y Jin High-Performance Simulation-Based Optimization, 165-187, 2020	18	2020
Surrogate-assisted evolutionary biobjective optimization for objectives with non-uniform latencies T Chugh, R Allmendinger, V Ojalehto, K Miettinen Proceedings of the genetic and evolutionary computation conference, 609-616, 2018	18	2018
On dealing with uncertainties from kriging models in offline data-driven evolutionary multiobjective optimization A Mazumdar, T Chugh, K Miettinen, M López-Ibáñez Evolutionary Multi-Criterion Optimization: 10th International Conference …, 2019	13	2019
Scalarizing functions in Bayesian multiobjective optimization T Chugh 2020 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2020	12	2020
Towards better integration of surrogate models and optimizers T Chugh, A Rahat, V Volz, M Zaefferer High-Performance Simulation-Based Optimization, 137-163, 2020	9	2020
On the impact of covariance functions in multi-objective Bayesian optimization for engineering design PS Palar, LR Zuhal, T Chugh, A Rahat AIAA Scitech 2020 Forum, 1867, 2020	8	2020
Multiobjective shape design in a ventilation system with a preference-driven surrogate-assisted evolutionary algorithm T Chugh, T Kratky, K Miettinen, Y Jin, P Makonen Proceedings of the Genetic and Evolutionary Computation Conference, 1147-1155, 2019	8	2019
K-RVEA: A Kriging-assisted evolutionary algorithm for many-objective optimization T Chugh, Y Jin, K Miettinen, J Hakanen, K Sindhya https://jyu.finna.fi/Record/jykdok.1544572, 2016	7	2016
Handling expensive multiobjective optimization problems with evolutionary algorithms T Chugh Jyväskylä studies in computing 263., 2017	6	2017

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