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Tinkle Chugh
Tinkle Chugh
Lecturer (Assistant Professor) in Computer Science, University of Exeter
Bestätigte E-Mail-Adresse bei exeter.ac.uk - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
4372018
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
4242016
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
258*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
1132017
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
992019
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
442017
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
352016
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
342016
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
322015
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
312014
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
292019
Scalarizing functions in Bayesian multiobjective optimization
T Chugh
2020 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2020
282020
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
262018
Surrogate-assisted evolutionary optimization of large problems
T Chugh, C Sun, H Wang, Y Jin
High-Performance Simulation-Based Optimization, 165-187, 2020
232020
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
162019
A visualizable test problem generator for many-objective optimization
JE Fieldsend, T Chugh, R Allmendinger, K Miettinen
IEEE Transactions on Evolutionary Computation 26 (1), 1-11, 2021
132021
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
102020
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
102019
Towards better integration of surrogate models and optimizers
T Chugh, A Rahat, V Volz, M Zaefferer
High-Performance Simulation-Based Optimization, 137-163, 2020
82020
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
82016
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