Rui Wang (王锐)
Rui Wang (王锐)
ACSE, The University of Sheffield / College of System Engineering, National University of Defense
Verified email at - Homepage
Cited by
Cited by
Preference-inspired Co-evolutionary Algorithms for Many-objective Optimisation
R Wang, R Purshouse, P Fleming
IEEE Transcation on Evolutionary Computation 17 (4), 474-491, 2013
Differential evolution with multi-population based ensemble of mutation strategies
G Wu, R Mallipeddi, PN Suganthan, R Wang, H Chen
Information Sciences 329, 329-345, 2016
Localized weighted sum method for many-objective optimization
R Wang, Z Zhou, H Ishibuchi, T Liao, T Zhang
IEEE Transactions on Evolutionary Computation, 2016
Decomposition-based algorithms using Pareto adaptive scalarizing methods
R Wang, Q Zhang, T Zhang
IEEE Transactions on Evolutionary Computation 20 (6), 821-837, 2016
Optimal operation of a smart residential microgrid based on model predictive control by considering uncertainties and storage impacts
Y Zhang, T Zhang, R Wang, Y Liu, B Guo
Solar Energy 122, 1052-1065, 2015
A review of hybrid evolutionary multiple criteria decision making methods
RC Purshouse, K Deb, MM Mansor, S Mostaghim, R Wang
2014 IEEE congress on evolutionary computation (CEC), 1147-1154, 2014
Multi-objective optimal design of hybrid renewable energy systems using preference-inspired coevolutionary approach
Z Shi, R Wang, T Zhang
Solar Energy 118, 96-106, 2015
Model predictive control-based operation management for a residential microgrid with considering forecast uncertainties and demand response strategies
Y Zhang, R Wang, T Zhang, Y Liu, B Guo
IET Generation, Transmission & Distribution 10 (10), 2367-2378, 2016
Preference-inspired co-evolutionary algorithms using weight vectors
R Wang, RC Purshouse, PJ Fleming
European Journal of Operational Research 243 (2), 423-441, 2015
A multi-objective co-evolutionary algorithm for energy-efficient scheduling on a green data center
H Lei, R Wang, T Zhang, Y Liu, Y Zha
Computers & Operations Research 75, 103-117, 2016
Evolutionary many-objective optimization: A comparative study of the state-of-the-art
K Li, R Wang, T Zhang, H Ishibuchi
IEEE Access 6, 26194-26214, 2018
On the effect of reference point in MOEA/D for multi-objective optimization
R Wang, J Xiong, H Ishibuchi, G Wu, T Zhang
Applied Soft Computing 58, 25-34, 2017
Optimal scheduling of track maintenance on a railway network
T Zhang, J Andrews, R Wang
Quality and Reliability Engineering International 29 (2), 285-297, 2013
General framework for localised multi-objective evolutionary algorithms
R Wang, PJ Fleming, RC Purshouse
Information sciences 258, 29-53, 2014
Multi-objective optimization of hybrid renewable energy system using an enhanced multi-objective evolutionary algorithm
M Ming, R Wang, Y Zha, T Zhang
Energies 10 (5), 674, 2017
Solving a multi-objective dynamic stochastic districting and routing problem with a co-evolutionary algorithm
H Lei, R Wang, G Laporte
Computers & Operations Research 67, 12-24, 2016
A stochastic MPC based approach to integrated energy management in microgrids
Y Zhang, F Meng, R Wang, W Zhu, XJ Zeng
Sustainable cities and society 41, 349-362, 2018
An efficient multi-objective model and algorithm for sizing a stand-alone hybrid renewable energy system
R Wang, G Li, M Ming, G Wu, L Wang
Energy 141, 2288-2299, 2017
Multi-clustering via evolutionary multi-objective optimization
R Wang, S Lai, G Wu, L Xing, L Wang, H Ishibuchi
Information Sciences 450, 128-140, 2018
Research and application of a novel hybrid model based on data selection and artificial intelligence algorithm for short term load forecasting
W Yang, J Wang, R Wang
Entropy 19 (2), 52, 2017
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