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总访问量

162

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  • 国内： 130

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1. Improving 1by1EA to Handle Various Shapes of Pareto Fronts [66]
2. A Double-Niched Evolutionary Algorithm and Its Behavior on Polygon.. [62]
3. Offline Automatic Parameter Tuning of MOEA/D Using Genetic Algorit.. [35]
4. A Scalable Indicator-Based Evolutionary Algorithm for Large-Scale .. [28]
5. Multi-modal Multi-objective Optimization: Problem Analysis and Cas.. [27]
6. A dual-grid dual-phase strategy for constrained multi-objective op.. [26]
7. Effects of Discretization of Decision and Objective Spaces on the .. [25]
8. Adapting Reference Vectors and Scalarizing Functions by Growing Ne.. [21]
9. Multiobjective data mining from solutions by evolutionary multiobj.. [21]
10. Topological Clustering via Adaptive Resonance Theory With Informat.. [20]
11. A Review of Evolutionary Multimodal Multiobjective Optimization [20]
12. Reference point specification in hypervolume calculation for fair .. [19]
13. Constrained multiobjective distance minimization problems [19]
14. A Hybrid Surrogate-Assisted Evolutionary Algorithm for Computation.. [19]
15. Reference Point Specification in Inverted Generational Distance fo.. [18]
16. How to Specify a Reference Point in Hypervolume Calculation for Fa.. [18]
17. R2-Based Hypervolume Contribution Approximation [18]
18. Dots-type constrained multiobjective distance minimization problem.. [18]
19. After 30 Years of Work in Osaka [Editor's Remarks] [17]
20. Non-elitist evolutionary multi-objective optimizers revisited [17]
21. An easy-to-use real-world multi-objective optimization problem sui.. [17]
22. Multi-clustering via evolutionary multi-objective optimization [16]
23. On the effect of reference point in MOEA/D for multi-objective opt.. [16]
24. Weight vector grid with new archive update mechanism for multi-obj.. [16]
25. A Study of the Naïve Objective Space Normalization Method in MOEA.. [16]
26. Use of Two Reference Points in Hypervolume-Based Evolutionary Mult.. [15]
27. Soft Computing Techniques for Dependable Cyber-Physical Systems [15]
28. Review and analysis of three components of the differential evolut.. [15]
29. On the effect of normalization in MOEA/D for multi-objective and m.. [14]
30. Incorporation of a decision space diversity maintenance mechanism .. [14]
31. A Study of the Naive Objective Space Normalization Method in MOEA/.. [14]
32. On the Normalization in Evolutionary Multi-Modal Multi-Objective O.. [14]
33. Use of Inverted Triangular Weight Vectors in Decomposition-Based M.. [13]
34. An analysis of control parameters of MOEA/D under two different op.. [13]
35. Benchmarking Multi- and Many-Objective Evolutionary Algorithms Und.. [13]
36. Handling Imbalance Between Convergence and Diversity in the Decisi.. [13]
37. Indicator-based weight adaptation for solving many-objective optim.. [13]
38. Many-objective problems are not always difficult for pareto domina.. [13]
39. Deep Takagi–Sugeno–Kang Fuzzy Classifier With Shared Linguistic .. [12]
40. End of Second Term as Editor-in-Chief [Editor's Remarks] [12]
41. Multiple Reference Points-Based Decomposition for Multiobjective F.. [12]
42. Weak Convergence Detection-based Dynamic Reference Point Specifica.. [12]
43. Reverse Strategy for Non-Dominated Archiving [12]
44. A Survey of Normalization Methods in Multiobjective Evolutionary A.. [12]
45. Hypervolume-Optimal μ-Distributions on Line/Plane-Based Pareto Fr.. [12]
46. A Networked ${N -Player Trust Game and Its Evolutionary Dynamics [11]
47. Stacked Blockwise Combination of Interpretable TSK Fuzzy Classifie.. [11]
48. Evolutionary Many-Objective Optimization: A Comparative Study of t.. [11]
49. Interactive Multiobjective Optimization: A Review of the State-of-.. [11]
50. Analysis of evolutionary multi-tasking as an island model [11]
51. IEEE CIM Survey Results [Editor's Remarks] [11]
52. Comparison of hypervolume, IGD and IGD+ from the viewpo.. [11]
53. Optimal Distributions of Solutions for Hypervolume Maximization on.. [11]
54. Development of a GUI tool for FML-based fuzzy system modeling [11]
55. A Grid-Based Inverted Generational Distance for Multi/Many-Objecti.. [11]
56. Multiobjective fuzzy genetics-based machine learning for multi-lab.. [11]
57. Performance Comparison of EMO Algorithms on Test Problems with Dif.. [10]
58. A niching indicator-based multi-modal many-objective optimizer [10]
59. A new R2 indicator for better hypervolume approximation [10]
60. Prof. Lotfi A. Zadeh [Editor's Remarks] [10]
61. One Year in China [Editor's Remarks] [10]
62. An Analysis of Quality Indicators Using Approximated Optimal Distr.. [10]
63. Dynamic Normalization in MOEA/D for Multiobjective optimization [10]
64. 進化型多目的マルチタスク最適化手法におけるタスク間交叉時の親個体が.. [10]
65. Guest Editorial Special Issue on Fuzzy Techniques in Financial Mod.. [9]
66. Last Editor's Remarks [Editor's Remarks] [9]
67. Smart World [Editor's Remarks] [9]
68. A Multiobjective Test Suite with Hexagon Pareto Fronts and Various.. [9]
69. Variable-depth adaptive large neighbourhood search algorithm for o.. [9]
70. A New Hypervolume-Based Evolutionary Algorithm for Many-Objective .. [9]
71. Simultaneous use of two normalization methods in decomposition-bas.. [9]
72. Lazy Greedy Hypervolume Subset Selection from Large Candidate Solu.. [9]
73. A Diversity-Enhanced Subset Selection Framework for Multimodal Mul.. [9]
74. Use of Two Penalty Values in Multiobjective Evolutionary Algorithm.. [9]
75. Dynamic Specification of a Reference Point for Hypervolume Calcula.. [8]
76. A Framework for Large-Scale Multiobjective Optimization Based on P.. [8]
77. Dual-grid model of MOEA/D for evolutionary constrained multiobject.. [8]
78. CIS Sponsored Conferences in 2019 [Editor's Remarks] [8]
79. Effect of Solution Information Sharing between Tasks on the Search.. [8]
80. A Framework to Handle Multimodal Multiobjective Optimization in De.. [8]
81. Decomposition-Based Multi-Objective Evolutionary Algorithm Design .. [8]
82. Modified Distance-based Subset Selection for Evolutionary Multi-ob.. [8]
83. A Decomposition-based Large-scale Multi-modal Multi-objective opti.. [8]
84. Effects of Local Mating in Inter-task Crossover on the Performance.. [8]
85. 未知クラスの継続的な学習を可能とするファジィ遺伝的機械学習手法 [8]
86. Realizing Deep High-order TSK Fuzzy Classifier by Ensembling Inter.. [8]
87. Metric for evaluating normalization methods in multiobjective opti.. [8]
88. Greedy approximated hypervolume subset selection for many-objectiv.. [8]
89. A Kernel-Based Indicator for Multi/Many-Objective Optimization [8]
90. Multi-Modal Multi-Objective Traveling Salesman Problem and its Evo.. [8]
91. Michigan-style Fuzzy GBML with (1+1)-ES Generation Update and Mult.. [7]
92. On Scalable Multiobjective Test Problems With Hardly Dominated Bou.. [7]
93. Joint Learning of Spectral Clustering Structure and Fuzzy Similari.. [7]
94. Topological Kernel Bayesian ARTMAP [7]
95. Stacked-Structure-Based Hierarchical Takagi-Sugeno-Kang Fuzzy Clas.. [7]
96. Use of inverted triangular weight vectors in decomposition-based m.. [7]
97. Optimizing Long-Term Bank Financial Products Portfolio Problems wi.. [7]
98. A New Monotone Fuzzy Rule Relabeling Framework With Application to.. [7]
99. Effects of dominance resistant solutions on the performance of evo.. [7]
100. Distance-based subset selection revisited [7]
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