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Furong Ye
Furong Ye
Verified email at liacs.leidenuniv.nl
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Cited by
Year
A novel forecasting method based on multi-order fuzzy time series and technical analysis
F Ye, L Zhang, D Zhang, H Fujita, Z Gong
Information Sciences 367, 41-57, 2016
1082016
A hybrid algorithm for a vehicle routing problem with realistic constraints
D Zhang, S Cai, F Ye, YW Si, TT Nguyen
Information Sciences 394, 167-182, 2017
892017
IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics
C Doerr, H Wang, F Ye, S van Rijn, T Bäck
arXiv preprint arXiv:1810.05281, 2018
672018
Benchmarking discrete optimization heuristics with IOHprofiler
C Doerr, F Ye, N Horesh, H Wang, OM Shir, T Bäck
Applied Soft Computing 18, 106027, 2020
602020
IOHanalyzer: Detailed performance analyses for iterative optimization heuristics
H Wang, D Vermetten, F Ye, C Doerr, T Bäck
ACM Transactions on Evolutionary Learning and Optimization 2 (1), 1-29, 2022
29*2022
Interpolating local and global search by controlling the variance of standard bit mutation
F Ye, C Doerr, T Bäck
2019 IEEE Congress on Evolutionary Computation (CEC), 2292-2299, 2019
222019
Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1+ λ) EA variants on onemax and leadingones
C Doerr, F Ye, S van Rijn, H Wang, T Bäck
Proceedings of the Genetic and Evolutionary Computation Conference, 951-958, 2018
192018
A hybrid algorithm based on variable neighbourhood for the strip packing problem
D Zhang, Y Che, F Ye, YW Si, SCH Leung
Journal of Combinatorial Optimization 32, 513-530, 2016
172016
A hybrid swarm algorithm based on ABC and AIS for 2L-HFCVRP
D Zhang, R Dong, YW Si, F Ye, Q Cai
Applied Soft Computing 64, 468-479, 2018
152018
Benchmarking a genetic algorithm with configurable crossover probability
F Ye, H Wang, C Doerr, T Bäck
Parallel Problem Solving from Nature–PPSN XVI: 16th International Conference …, 2020
122020
Automated configuration of genetic algorithms by tuning for anytime performance
F Ye, C Doerr, H Wang, T Bäck
IEEE Transactions on Evolutionary Computation 26 (6), 1526-1538, 2022
102022
Leveraging benchmarking data for informed one-shot dynamic algorithm selection
F Ye, C Doerr, T Bäck
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021
42021
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics
J de Nobel, F Ye, D Vermetten, H Wang, C Doerr, T Bäck
arXiv preprint arXiv:2111.04077, 2021
32021
Non-elitist selection can improve the performance of irace
F Ye, D Vermetten, C Doerr, T Bäck
Parallel Problem Solving from Nature–PPSN XVII: 17th International …, 2022
1*2022
Discrete differential evolutionary algorithm for job-shop scheduling problem with minimizing total weighted tardiness
F Ye, Z You, D Zhang, SCH Leung
2016 IEEE Congress on Evolutionary Computation (CEC), 56-62, 2016
12016
What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms
F Ye, F Neumann, J de Nobel, A Neumann, T Bäck
arXiv preprint arXiv:2303.04611, 2023
2023
Using Affine Combinations of BBOB Problems for Performance Assessment
D Vermetten, F Ye, C Doerr
arXiv preprint arXiv:2303.04573, 2023
2023
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler
F Neumann, A Neumann, C Qian, VA Do, J de Nobel, D Vermetten, ...
arXiv preprint arXiv:2302.01464, 2023
2023
IOHanalyzer: Detailed performance analyses for iterative optimization heuristics: hot-off-the-press track@ GECCO 2022
H Wang, D Vermetten, F Ye, C Doerr, T Bäck
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022
2022
Automated configuration of genetic algorithms by tuning for anytime performance: hot-off-the-press track at GECCCO 2022
F Ye, C Doerr, H Wang, T Bäck
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022
2022
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