| An improved shuffled frog-leaping algorithm with extremal optimisation for continuous optimisation X Li, J Luo, MR Chen, N Wang Information Sciences 192, 143-151, 2012 | 134 | 2012 |
| An artificial bee colony algorithm for multi-objective optimisation J Luo, Q Liu, Y Yang, X Li, M Chen, W Cao Applied Soft Computing 50, 235-251, 2017 | 115 | 2017 |
| A novel hybrid shuffled frog leaping algorithm for vehicle routing problem with time windows J Luo, X Li, MR Chen, H Liu Information Sciences 316, 266-292, 2015 | 107 | 2015 |
| Evolutionary optimization of expensive multiobjective problems with co-sub-Pareto front Gaussian process surrogates J Luo, A Gupta, YS Ong, Z Wang IEEE transactions on cybernetics 49 (5), 1708-1721, 2018 | 94 | 2018 |
| Hybrid shuffled frog leaping algorithm for energy-efficient dynamic consolidation of virtual machines in cloud data centers J Luo, X Li, M Chen Expert Systems with Applications 41 (13), 5804-5816, 2014 | 92 | 2014 |
| Improved shuffled frog leaping algorithm and its multi-phase model for multi-depot vehicle routing problem J Luo, MR Chen Expert Systems with Applications 41 (5), 2535-2545, 2014 | 85 | 2014 |
| Multi-phase modified shuffled frog leaping algorithm with extremal optimization for the MDVRP and the MDVRPTW J Luo, MR Chen Computers & Industrial Engineering 72, 84-97, 2014 | 69 | 2014 |
| Choose appropriate subproblems for collaborative modeling in expensive multiobjective optimization Z Wang, Q Zhang, YS Ong, S Yao, H Liu, J Luo IEEE Transactions on Cybernetics 53 (1), 483-496, 2021 | 52 | 2021 |
| A many-objective particle swarm optimizer based on indicator and direction vectors for many-objective optimization J Luo, X Huang, Y Yang, X Li, Z Wang, J Feng Information Sciences 514, 166-202, 2020 | 49 | 2020 |
| A new hybrid memetic multi-objective optimization algorithm for multi-objective optimization J Luo, Y Yang, Q Liu, X Li, M Chen, K Gao Information Sciences 448, 164-186, 2018 | 36 | 2018 |
| A decomposition-based multi-objective evolutionary algorithm with quality indicator J Luo, Y Yang, X Li, Q Liu, M Chen, K Gao Swarm and evolutionary computation 39, 339-355, 2018 | 36 | 2018 |
| Discrete harmony search algorithm for scheduling and rescheduling the reprocessing problems in remanufacturing: a case study K Gao, L Wang, J Luo, H Jiang, A Sadollah, Q Pan Engineering Optimization 50 (6), 965-981, 2018 | 26 | 2018 |
| Map navigation system based on optimal Dijkstra algorithm C Ruan, J Luo, Y Wu 2014 IEEE 3rd International conference on cloud computing and intelligence …, 2014 | 26 | 2014 |
| Balancing performance between the decision space and the objective space in multimodal multiobjective optimization Q Yang, Z Wang, J Luo, Q He Memetic computing 13 (1), 31-47, 2021 | 25 | 2021 |
| Improved shuffled frog leaping algorithm for solving CVRP JP Luo, X Li, MR Chen 电子与信息学报 33 (2), 429-434, 2011 | 25 | 2011 |
| Improved jaya algorithm for flexible job shop rescheduling problem K Gao, F Yang, J Li, H Sang, J Luo IEEE Access 8, 86915-86922, 2020 | 23 | 2020 |
| The Markov model of shuffled frog leaping algorithm and its convergence analysis J Luo, X Li, M Chen Dianzi Xuebao(Acta Electronica Sinica) 38 (12), 2875-2880, 2010 | 22 | 2010 |
| Novel multitask conditional neural-network surrogate models for expensive optimization J Luo, L Chen, X Li, Q Zhang IEEE Transactions on Cybernetics 52 (5), 3984-3997, 2020 | 16 | 2020 |
| Multi-phase meta-heuristic for multi-depots vehicle routing problem J Luo, X Li, MR Chen Journal of Software Engineering and Applications 6 (3), 82-86, 2013 | 15 | 2013 |
| Expensive multiobjective optimization based on information transfer surrogate J Luo, YF Dong, Z Zhu, W Cao, X Li IEEE Transactions on Systems, Man, and Cybernetics: Systems 53 (3), 1684-1696, 2022 | 14 | 2022 |
Kaizhou GaoMacau University of Science and Technologyยืนยันอีเมลแล้วที่ e.ntu.edu.sg