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3653

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1. A Novel Dual-Stage Dual-Population Evolutionary Algorithm for Cons.. [205]
2. A Scalable Indicator-Based Evolutionary Algorithm for Large-Scale .. [203]
3. A Double-Niched Evolutionary Algorithm and Its Behavior on Polygon.. [177]
4. Comparison of hypervolume, IGD and IGD+ from the viewpo.. [169]
5. Improving 1by1EA to Handle Various Shapes of Pareto Fronts [164]
6. A dual-grid dual-phase strategy for constrained multi-objective op.. [162]
7. Soft Computing Techniques for Dependable Cyber-Physical Systems [161]
8. Multi-modal Multi-objective Optimization: Problem Analysis and Cas.. [157]
9. Offline Automatic Parameter Tuning of MOEA/D Using Genetic Algorit.. [145]
10. Weak Convergence Detection-based Dynamic Reference Point Specifica.. [144]
11. Dynamic Normalization in MOEA/D for Multiobjective optimization [140]
12. Indicator-based weight adaptation for solving many-objective optim.. [137]
13. A Study of the Naïve Objective Space Normalization Method in MOEA.. [137]
14. CIM Editorial Board [136]
15. 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 [135]
16. After 30 Years of Work in Osaka [Editor's Remarks] [134]
17. Optimal Distributions of Solutions for Hypervolume Maximization on.. [133]
18. Lazy Greedy Hypervolume Subset Selection from Large Candidate Solu.. [131]
19. An easy-to-use real-world multi-objective optimization problem sui.. [129]
20. IEEE CIM Survey Results [Editor's Remarks] [128]
21. R2-Based Hypervolume Contribution Approximation [128]
22. A Grid-Based Inverted Generational Distance for Multi/Many-Objecti.. [128]
23. One Year in China [Editor's Remarks] [126]
24. Effects of Discretization of Decision and Objective Spaces on the .. [126]
25. Effects of Local Mating in Inter-task Crossover on the Performance.. [126]
26. Analysis of evolutionary multi-tasking as an island model [125]
27. A Hybrid Surrogate-Assisted Evolutionary Algorithm for Computation.. [125]
28. Simultaneous use of two normalization methods in decomposition-bas.. [125]
29. Topological Clustering via Adaptive Resonance Theory With Informat.. [122]
30. Constrained multiobjective distance minimization problems [122]
31. Effect of Solution Information Sharing between Tasks on the Search.. [122]
32. A Multiobjective Test Suite with Hexagon Pareto Fronts and Various.. [121]
33. A Study of the Naive Objective Space Normalization Method in MOEA/.. [121]
34. A Survey of Normalization Methods in Multiobjective Evolutionary A.. [121]
35. A New Monotone Fuzzy Rule Relabeling Framework With Application to.. [120]
36. Decomposition-Based Multi-Objective Evolutionary Algorithm Design .. [120]
37. End of Second Term as Editor-in-Chief [Editor's Remarks] [119]
38. 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.. [119]
39. A Review of Evolutionary Multimodal Multiobjective Optimization [116]
40. Last Editor's Remarks [Editor's Remarks] [114]
41. Smart World [Editor's Remarks] [114]
42. A new R2 indicator for better hypervolume approximation [113]
43. Prof. Lotfi A. Zadeh [Editor's Remarks] [113]
44. Multi-clustering via evolutionary multi-objective optimization [112]
45. Development of a GUI tool for FML-based fuzzy system modeling [112]
46. Multiobjective Fuzzy Genetics-Based Machine Learning based on MOEA.. [111]
47. Riesz s-energy-based Reference Sets for Multi-Objective optimizati.. [111]
48. Non-elitist evolutionary multi-objective optimizers revisited [110]
49. Another difficulty of inverted triangular pareto fronts for decomp.. [110]
50. Interactive Multiobjective Optimization: A Review of the State-of-.. [108]
51. Cashless Society [Editor's Remarks] [108]
52. A New Hypervolume-Based Evolutionary Algorithm for Many-Objective .. [108]
53. A Note on Constrained Multi-Objective Optimization Benchmark Probl.. [107]
54. Incorporation of a decision space diversity maintenance mechanism .. [107]
55. Reference point specification in hypervolume calculation for fair .. [107]
56. CIM Editorial Board [107]
57. Modified Distance-based Subset Selection for Evolutionary Multi-ob.. [107]
58. An analysis of control parameters of MOEA/D under two different op.. [106]
59. Review and analysis of three components of the differential evolut.. [106]
60. Regular Pareto Front Shape is not Realistic [106]
61. Reverse Strategy for Non-Dominated Archiving [106]
62. A Decomposition-based Large-scale Multi-modal Multi-objective opti.. [106]
63. AI and CI [Editor's Remarks] [105]
64. Algorithm Configurations of MOEA/D with an Unbounded External Arch.. [105]
65. Population Size Specification for Fair Comparison of Multi-objecti.. [105]
66. On Scalable Multiobjective Test Problems With Hardly Dominated Bou.. [104]
67. Optimizing Long-Term Bank Financial Products Portfolio Problems wi.. [104]
68. On the Normalization in Evolutionary Multi-Modal Multi-Objective O.. [104]
69. Guest Editorial Special Issue on Fuzzy Techniques in Financial Mod.. [103]
70. Handling Imbalance Between Convergence and Diversity in the Decisi.. [103]
71. CIS Sponsored Conferences in 2019 [Editor's Remarks] [103]
72. A Framework to Handle Multimodal Multiobjective Optimization in De.. [103]
73. Dots-type constrained multiobjective distance minimization problem.. [101]
74. Multiobjective fuzzy genetics-based machine learning for multi-lab.. [101]
75. On the effect of normalization in MOEA/D for multi-objective and m.. [100]
76. Multi-label Classification Based on Adaptive Resonance Theory [100]
77. Weight vector grid with new archive update mechanism for multi-obj.. [99]
78. A niching indicator-based multi-modal many-objective optimizer [98]
79. Guest Editorial Evolutionary Many-Objective Optimization [98]
80. Use of inverted triangular weight vectors in decomposition-based m.. [98]
81. Many-objective problems are not always difficult for pareto domina.. [97]
82. Numerical Analysis on Optimal Distributions of Solutions for Hyper.. [97]
83. Multilayer Clustering Based on Adaptive Resonance Theory for Noisy.. [96]
84. Adapting Reference Vectors and Scalarizing Functions by Growing Ne.. [95]
85. A Survey on the Hypervolume Indicator in Evolutionary Multiobjecti.. [95]
86. Reference Point Specification in Inverted Generational Distance fo.. [94]
87. Dual-grid model of MOEA/D for evolutionary constrained multiobject.. [93]
88. Benchmarking Multi- and Many-Objective Evolutionary Algorithms Und.. [92]
89. Use of Two Reference Points in Hypervolume-Based Evolutionary Mult.. [91]
90. Effects of dominance resistant solutions on the performance of evo.. [91]
91. Weighted Indicator-Based Evolutionary Algorithm for Multimodal Mul.. [91]
92. Performance Comparison of Multiobjective Evolutionary Algorithms o.. [89]
93. Performance Comparison of EMO Algorithms on Test Problems with Dif.. [89]
94. How to Specify a Reference Point in Hypervolume Calculation for Fa.. [89]
95. On the effect of reference point in MOEA/D for multi-objective opt.. [89]
96. Divisive Hierarchical Clustering Based on Adaptive Resonance Theor.. [89]
97. Michigan-style Fuzzy GBML with (1+1)-ES Generation Update and Mult.. [88]
98. Variable-depth adaptive large neighbourhood search algorithm for o.. [88]
99. Evolutionary Many-Objective Optimization: A Comparative Study of t.. [87]
100. Difficulties in Fair Performance Comparison of Multi-Objective Evo.. [87]
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