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ORCIDHisao Ishibuchi
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- affiliation: Southern University of Science and Technology, Shenzhen, China
- affiliation: Osaka Prefecture University, Japan
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2020 – today
- 2022
[j150]Jose Maria Alonso-Moral, Corrado Mencar, Hisao Ishibuchi:
Explainable and Trustworthy Artificial Intelligence [Guest Editorial]. IEEE Comput. Intell. Mag. 17(1): 14-15 (2022)- [j149]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Difficulties in Fair Performance Comparison of Multi-Objective Evolutionary Algorithms [Research Frontier]. IEEE Comput. Intell. Mag. 17(1): 86-101 (2022) - [j148]Xiongtao Zhang
, Yusuke Nojima, Hisao Ishibuchi, Wenjun Hu, Shitong Wang:
Prediction by Fuzzy Clustering and KNN on Validation Data With Parallel Ensemble of Interpretable TSK Fuzzy Classifiers. IEEE Trans. Syst. Man Cybern. Syst. 52(1): 400-414 (2022) - 2021
- [j147]Ke Shang, Hisao Ishibuchi, Linjun He, Lie Meng Pang:
A Survey on the Hypervolume Indicator in Evolutionary Multiobjective Optimization. IEEE Trans. Evol. Comput. 25(1): 1-20 (2021) - [j146]Xinye Cai, Yushun Xiao, Miqing Li, Han Hu, Hisao Ishibuchi, Xiaoping Li:
A Grid-Based Inverted Generational Distance for Multi/Many-Objective Optimization. IEEE Trans. Evol. Comput. 25(1): 21-34 (2021) - [j145]Jesús Guillermo Falcón-Cardona, Hisao Ishibuchi, Carlos A. Coello Coello, Michael Emmerich:
On the Effect of the Cooperation of Indicator-Based Multiobjective Evolutionary Algorithms. IEEE Trans. Evol. Comput. 25(4): 681-695 (2021) - [j144]Linjun He, Hisao Ishibuchi, Anupam Trivedi, Handing Wang, Yang Nan, Dipti Srinivasan:
A Survey of Normalization Methods in Multiobjective Evolutionary Algorithms. IEEE Trans. Evol. Comput. 25(6): 1028-1048 (2021) - [j143]Wenhua Li, Tao Zhang, Rui Wang, Hisao Ishibuchi:
Weighted Indicator-Based Evolutionary Algorithm for Multimodal Multiobjective Optimization. IEEE Trans. Evol. Comput. 25(6): 1064-1078 (2021) - [j142]Suhang Gu, Yusuke Nojima, Hisao Ishibuchi, Shitong Wang:
Fuzzy Style K-Plane Clustering. IEEE Trans. Fuzzy Syst. 29(6): 1518-1532 (2021) - [j141]Te Zhang, Zhaohong Deng, Hisao Ishibuchi, Lie Meng Pang:
Robust TSK Fuzzy System Based on Semisupervised Learning for Label Noise Data. IEEE Trans. Fuzzy Syst. 29(8): 2145-2157 (2021) - [j140]Bin Qin, Yusuke Nojima, Hisao Ishibuchi, Shitong Wang:
Realizing Deep High-Order TSK Fuzzy Classifier by Ensembling Interpretable Zero-Order TSK Fuzzy Subclassifiers. IEEE Trans. Fuzzy Syst. 29(11): 3441-3455 (2021) - [c332]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Using a Genetic Algorithm-based Hyper-heuristic to Tune MOEA/D for a Set of Various Test Problems. CEC 2021: 1486-1494 - [c331]Longcan Chen, Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Periodical Generation Update using an Unbounded External Archive for Multi-Objective Optimization. CEC 2021: 1912-1920 - [c330]Yang Nan, Ke Shang, Hisao Ishibuchi, Linjun He:
A Two-stage Hypervolume Contribution Approximation Method Based on R2 Indicator. CEC 2021: 2468-2475 - [c329]Qite Yang, Zhenkun Wang, Hisao Ishibuchi:
It Is Hard to Distinguish Between Dominance Resistant Solutions and Extremely Convex Pareto Optimal Solutions. EMO 2021: 3-14 - [c328]Ke Shang, Hisao Ishibuchi, Longcan Chen, Weiyu Chen, Lie Meng Pang:
Improving the Efficiency of R2HCA-EMOA. EMO 2021: 115-125 - [c327]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Using a Genetic Algorithm-Based Hyper-Heuristic to Tune MOEA/D for a Set of Benchmark Test Problems. EMO 2021: 164-177 - [c326]Yiming Peng, Hisao Ishibuchi:
Niching Diversity Estimation for Multi-modal Multi-objective Optimization. EMO 2021: 323-334 - [c325]Jinyuan Zhang, Hisao Ishibuchi:
Multiobjective Optimization with Fuzzy Classification-Assisted Environmental Selection. EMO 2021: 580-592 - [c324]Yifan Wang, Hisao Ishibuchi, Jihua Zhu, Yaxiong Wang, Tao Dai:
Unsupervised Fuzzy Neural Network for Image Clustering. FUZZ-IEEE 2021: 1-6 - [c323]Linjun He, Hisao Ishibuchi, Dipti Srinivasan:
Metric for evaluating normalization methods in multiobjective optimization. GECCO 2021: 403-411 - [c322]Ke Shang, Hisao Ishibuchi, Yang Nan:
Distance-based subset selection revisited. GECCO 2021: 439-447 - [c321]Ke Shang, Hisao Ishibuchi, Weiyu Chen:
Greedy approximated hypervolume subset selection for many-objective optimization. GECCO 2021: 448-456 - [c320]Jinyuan Zhang, Hisao Ishibuchi, Ke Shang, Linjun He, Lie Meng Pang, Yiming Peng:
Environmental selection using a fuzzy classifier for multiobjective evolutionary algorithms. GECCO 2021: 485-492 - [c319]Yiming Peng, Hisao Ishibuchi:
A Decomposition-based Hybrid Evolutionary Algorithm for Multi-modal Multi-objective Optimization. SMC 2021: 160-167 - [c318]Ke Shang, Hisao Ishibuchi, Lie Meng Pang, Yang Nan:
Reference Point Specification for Greedy Hypervolume Subset Selection. SMC 2021: 168-175 - [c317]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Clustering-Based Subset Selection in Evolutionary Multiobjective Optimization. SMC 2021: 468-475 - [c316]Lie Meng Pang, Ke Shang, Longcan Chen, Hisao Ishibuchi, Weiyu Chen:
Proposal of a New Test Problem for Large-Scale Multi- and Many-Objective Optimization. SMC 2021: 484-491 - [c315]Yang Nan, Ke Shang, Hisao Ishibuchi, Linjun He:
Improving Local Search Hypervolume Subset Selection in Evolutionary Multi-objective Optimization. SMC 2021: 751-757 - [c314]Yiping Liu, Liting Xu, Yuyan Han, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi, Gary G. Yen:
Multi-Modal Multi-Objective Traveling Salesman Problem and its Evolutionary Optimizer. SMC 2021: 770-777 - [e6]Hisao Ishibuchi, Qingfu Zhang, Ran Cheng, Ke Li, Hui Li, Handing Wang, Aimin Zhou:
Evolutionary Multi-Criterion Optimization - 11th International Conference, EMO 2021, Shenzhen, China, March 28-31, 2021, Proceedings. Lecture Notes in Computer Science 12654, Springer 2021, ISBN 978-3-030-72061-2 [contents] - [i25]Yiming Peng, Hisao Ishibuchi:
Niching Diversity Estimation for Multi-modal Multi-objective Optimization. CoRR abs/2102.00383 (2021) - [i24]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Fast Greedy Subset Selection from Large Candidate Solution Sets in Evolutionary Multi-objective Optimization. CoRR abs/2102.00941 (2021) - [i23]Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi:
Multi-label Classification via Adaptive Resonance Theory-based Clustering. CoRR abs/2103.01511 (2021) - [i22]Ke Shang, Hisao Ishibuchi, Weiyu Chen, Yang Nan, Weiduo Liao:
Hypervolume-Optimal μ-Distributions on Line/Plane-based Pareto Fronts in Three Dimensions. CoRR abs/2104.09736 (2021) - [i21]Rahul Kumar Sevakula, Nishchal Kumar Verma, Hisao Ishibuchi:
On fine-tuning of Autoencoders for Fuzzy rule classifiers. CoRR abs/2106.11182 (2021) - [i20]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Clustering-Based Subset Selection in Evolutionary Multiobjective Optimization. CoRR abs/2108.08453 (2021) - 2020
- [j139]Yang Nan, Ke Shang, Hisao Ishibuchi, Linjun He:
Reverse Strategy for Non-Dominated Archiving. IEEE Access 8: 119458-119469 (2020) - [j138]Lie Meng Pang, Kai Meng Tay, Chee Peng Lim, Hisao Ishibuchi:
A New Monotone Fuzzy Rule Relabeling Framework With Application to Failure Mode and Effect Analysis Methodology. IEEE Access 8: 144908-144930 (2020) - [j137]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Decomposition-Based Multi-Objective Evolutionary Algorithm Design Under Two Algorithm Frameworks. IEEE Access 8: 163197-163208 (2020) - [j136]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
NSGA-II With Simple Modification Works Well on a Wide Variety of Many-Objective Problems. IEEE Access 8: 190240-190250 (2020) - [j135]Ryoji Tanabe, Hisao Ishibuchi:
An easy-to-use real-world multi-objective optimization problem suite. Appl. Soft Comput. 89: 106078 (2020) - [j134]Linjun He, Ke Shang, Hisao Ishibuchi:
Simultaneous use of two normalization methods in decomposition-based multi-objective evolutionary algorithms. Appl. Soft Comput. 92: 106316 (2020) - [j133]Jian Xiong, Chao Zhang, Gang Kou, Rui Wang, Hisao Ishibuchi, Fawaz E. Alsaadi:
Optimizing Long-Term Bank Financial Products Portfolio Problems with a Multiobjective Evolutionary Approach. Complex. 2020: 3106097:1-3106097:18 (2020) - [j132]Bach Hoai Nguyen, Bing Xue, Peter Andreae, Hisao Ishibuchi, Mengjie Zhang:
Multiple Reference Points-Based Decomposition for Multiobjective Feature Selection in Classification: Static and Dynamic Mechanisms. IEEE Trans. Evol. Comput. 24(1): 170-184 (2020) - [j131]Ke Shang, Hisao Ishibuchi, Xizi Ni:
R2-Based Hypervolume Contribution Approximation. IEEE Trans. Evol. Comput. 24(1): 185-192 (2020) - [j130]Ryoji Tanabe, Hisao Ishibuchi:
A Review of Evolutionary Multimodal Multiobjective Optimization. IEEE Trans. Evol. Comput. 24(1): 193-200 (2020) - [j129]Yiping Liu, Hisao Ishibuchi, Naoki Masuyama, Yusuke Nojima:
Adapting Reference Vectors and Scalarizing Functions by Growing Neural Gas to Handle Irregular Pareto Fronts. IEEE Trans. Evol. Comput. 24(3): 439-453 (2020) - [j128]Yiping Liu, Hisao Ishibuchi, Gary G. Yen, Yusuke Nojima, Naoki Masuyama:
Handling Imbalance Between Convergence and Diversity in the Decision Space in Evolutionary Multimodal Multiobjective Optimization. IEEE Trans. Evol. Comput. 24(3): 551-565 (2020) - [j127]Ryoji Tanabe, Hisao Ishibuchi:
A Framework to Handle Multimodal Multiobjective Optimization in Decomposition-Based Evolutionary Algorithms. IEEE Trans. Evol. Comput. 24(4): 720-734 (2020) - [j126]Ke Shang, Hisao Ishibuchi, Xizi Ni:
Erratum to "R2-Based Hypervolume Contribution Approximation". IEEE Trans. Evol. Comput. 24(4): 807 (2020) - [j125]Ke Shang, Hisao Ishibuchi:
A New Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization. IEEE Trans. Evol. Comput. 24(5): 839-852 (2020) - [j124]Ryoji Tanabe, Hisao Ishibuchi:
An Analysis of Quality Indicators Using Approximated Optimal Distributions in a 3-D Objective Space. IEEE Trans. Evol. Comput. 24(5): 853-867 (2020) - [j123]Suhang Gu, Yusuke Nojima, Hisao Ishibuchi, Shitong Wang:
A Novel Classification Method From the Perspective of Fuzzy Social Networks Based on Physical and Implicit Style Features of Data. IEEE Trans. Fuzzy Syst. 28(2): 361-375 (2020) - [c313]Yuna Yamada, Naoki Masuyama, Narito Amako, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi:
Divisive Hierarchical Clustering Based on Adaptive Resonance Theory. CcS 2020: 1-6 - [c312]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Modified Distance-based Subset Selection for Evolutionary Multi-objective Optimization Algorithms. CEC 2020: 1-8 - [c311]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Lazy Greedy Hypervolume Subset Selection from Large Candidate Solution Sets. CEC 2020: 1-8 - [c310]Jesús Guillermo Falcón-Cardona, Hisao Ishibuchi, Carlos A. Coello Coello:
Riesz s-energy-based Reference Sets for Multi-Objective optimization. CEC 2020: 1-8 - [c309]Ryuichi Hashimoto, Toshiki Urita, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
Effects of Local Mating in Inter-task Crossover on the Performance of Decomposition-based Evolutionary Multiobjective Multitask optimization Algorithms. CEC 2020: 1-8 - [c308]Linjun He, Hisao Ishibuchi, Anupam Trivedi, Dipti Srinivasan:
Dynamic Normalization in MOEA/D for Multiobjective optimization. CEC 2020: 1-8 - [c307]Yiping Liu, Hisao Ishibuchi, Gary G. Yen, Yusuke Nojima, Naoki Masuyama, Yuyan Han:
On the Normalization in Evolutionary Multi-Modal Multi-Objective Optimization. CEC 2020: 1-8 - [c306]Yiming Peng, Hisao Ishibuchi:
A Decomposition-based Large-scale Multi-modal Multi-objective optimization Algorithm. CEC 2020: 1-8 - [c305]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
A New Framework of Evolutionary Multi-Objective Algorithms with an Unbounded External Archive. ECAI 2020: 283-290 - [c304]Hisao Ishibuchi, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima:
Many-Objective Problems Are Not Always Difficult for Pareto Dominance-Based Evolutionary Algorithms. ECAI 2020: 291-298 - [c303]Yuichi Omozaki, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
Multiobjective Fuzzy Genetics-Based Machine Learning for Multi-Label Classification. FUZZ-IEEE 2020: 1-8 - [c302]Hisao Ishibuchi, Hiroyuki Sato:
Evolutionary many-objective optimization. GECCO Companion 2020: 428-457 - [c301]Linjun He, Auraham Camacho, Hisao Ishibuchi:
Another difficulty of inverted triangular pareto fronts for decomposition-based multi-objective algorithms. GECCO 2020: 498-506 - [c300]Hisao Ishibuchi, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima:
Effects of dominance resistant solutions on the performance of evolutionary multi-objective and many-objective algorithms. GECCO 2020: 507-515 - [c299]Yang Nan, Ke Shang, Hisao Ishibuchi:
What is a good direction vector set for the R2-based hypervolume contribution approximation. GECCO 2020: 524-532 - [c298]Narito Amako, Naoki Masuyama, Chu Kiong Loo, Yusuke Nojima, Yiping Liu, Hisao Ishibuchi:
Multilayer Clustering Based on Adaptive Resonance Theory for Noisy Environments. IJCNN 2020: 1-8 - [c297]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Proposal of a Realistic Many-Objective Test Suite. PPSN (1) 2020: 201-214 - [c296]Ke Shang, Hisao Ishibuchi, Weiyu Chen, Lukás Adam:
Hypervolume Optimal μ-Distributions on Line-Based Pareto Fronts in Three Dimensions. PPSN (2) 2020: 257-270 - [c295]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Algorithm Configurations of MOEA/D with an Unbounded External Archive. SMC 2020: 1087-1094 - [c294]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Population Size Specification for Fair Comparison of Multi-objective Evolutionary Algorithms. SMC 2020: 1095-1102 - [c293]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Numerical Analysis on Optimal Distributions of Solutions for Hypervolume Maximization. SMC 2020: 1103-1110 - [c292]Weiduo Liao, Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Parallel Implementation of MOEA/D with Parallel Weight Vectors for Feature Selection. SMC 2020: 1524-1531 - [c291]Jesús Guillermo Falcón-Cardona, Hisao Ishibuchi, Carlos A. Coello Coello:
Exploiting the Trade-off between Convergence and Diversity Indicators. SSCI 2020: 141-148 - [c290]Ke Shang, Hisao Ishibuchi, Yang Nan, Weiyu Chen:
Transformation-based Hypervolume Indicator: A Framework for Designing Hypervolume Variants. SSCI 2020: 157-164 - [c289]Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi:
Multi-label Classification Based on Adaptive Resonance Theory. SSCI 2020: 1913-1920 - [c288]Longcan Chen, Ke Shang, Hisao Ishibuchi:
Performance Comparison of Multi-Objective Evolutionary Algorithms on Simple and Difficult Many-Objective Test Problems. SSCI 2020: 2461-2468 - [i19]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Effects of Discretization of Decision and Objective Spaces on the Performance of Evolutionary Multiobjective Optimization Algorithms. CoRR abs/2003.09917 (2020) - [i18]Yiming Peng, Hisao Ishibuchi:
A Decomposition-based Large-scale Multi-modal Multi-objective Optimization Algorithm. CoRR abs/2004.09838 (2020) - [i17]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Solution Subset Selection for Final Decision Making in Evolutionary Multi-Objective Optimization. CoRR abs/2006.08156 (2020) - [i16]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Lazy Greedy Hypervolume Subset Selection from Large Candidate Solution Sets. CoRR abs/2007.02050 (2020) - [i15]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Algorithm Configurations of MOEA/D with an Unbounded External Archive. CoRR abs/2007.13352 (2020) - [i14]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Decomposition-Based Multi-Objective Evolutionary Algorithm Design under Two Algorithm Frameworks. CoRR abs/2008.07094 (2020) - [i13]Ryoji Tanabe, Hisao Ishibuchi:
An Analysis of Quality Indicators Using Approximated Optimal Distributions in a Three-dimensional Objective Space. CoRR abs/2009.12788 (2020) - [i12]Ryoji Tanabe, Hisao Ishibuchi:
An Easy-to-use Real-world Multi-objective Optimization Problem Suite. CoRR abs/2009.12867 (2020) - [i11]Ryoji Tanabe, Hisao Ishibuchi:
A Review of Evolutionary Multi-modal Multi-objective Optimization. CoRR abs/2009.13347 (2020) - [i10]Ryoji Tanabe, Hisao Ishibuchi:
A Framework to Handle Multi-modal Multi-objective Optimization in Decomposition-based Evolutionary Algorithms. CoRR abs/2009.14700 (2020) - [i9]Ryoji Tanabe, Hisao Ishibuchi:
Non-elitist Evolutionary Multi-objective Optimizers Revisited. CoRR abs/2009.14717 (2020) - [i8]Ryoji Tanabe, Hisao Ishibuchi:
A Niching Indicator-Based Multi-modal Many-objective Optimizer. CoRR abs/2010.00236 (2020) - [i7]Ryoji Tanabe, Hisao Ishibuchi:
Review and Analysis of Three Components of Differential Evolution Mutation Operator in MOEA/D-DE. CoRR abs/2010.00265 (2020) - [i6]Ryoji Tanabe, Hisao Ishibuchi:
An Analysis of Control Parameters of MOEA/D Under Two Different Optimization Scenarios. CoRR abs/2010.00818 (2020) - [i5]Hisao Ishibuchi, Lie Meng Pang, Ke Shang:
Evolutionary Multi-Objective Optimization Algorithm Framework with Three Solution Sets. CoRR abs/2012.07319 (2020)
2010 – 2019
- 2019
- [j122]Muhammad Atif, Siddique Latif, Rizwan Ahmad, Adnan Khalid Kiani, Junaid Qadir, Adeel Baig, Hisao Ishibuchi, Waseem Abbas:
Soft Computing Techniques for Dependable Cyber-Physical Systems. IEEE Access 7: 72030-72049 (2019) - [j121]Naoki Masuyama, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota, Yusuke Nojima, Yiping Liu:
Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning. IEEE Access 7: 76920-76936 (2019) - [j120]Hisao Ishibuchi:
Prof. Lotfi A. Zadeh [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(1): 2 (2019) - [j119]Hisao Ishibuchi:
Cashless Society [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(2): 2 (2019) - [j118]Hisao Ishibuchi:
AI and CI [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(3): 2 (2019) - [j117]Hisao Ishibuchi:
Last Editor's Remarks [Editor's Remarks]. IEEE Comput. Intell. Mag. 14(4): 2 (2019) - [j116]Ryoji Tanabe, Hisao Ishibuchi:
Review and analysis of three components of the differential evolution mutation operator in MOEA/D-DE. Soft Comput. 23(23): 12843-12857 (2019) - [j115]Ryoji Tanabe, Hisao Ishibuchi:
A niching indicator-based multi-modal many-objective optimizer. Swarm Evol. Comput. 49: 134-146 (2019) - [j114]Zhenkun Wang, Yew-Soon Ong, Hisao Ishibuchi:
On Scalable Multiobjective Test Problems With Hardly Dominated Boundaries. IEEE Trans. Evol. Comput. 23(2): 217-231 (2019) - [j113]Wenjing Hong, Ke Tang, Aimin Zhou, Hisao Ishibuchi, Xin Yao:
A Scalable Indicator-Based Evolutionary Algorithm for Large-Scale Multiobjective Optimization. IEEE Trans. Evol. Comput. 23(3): 525-537 (2019) - [j112]Zekang Bian, Hisao Ishibuchi, Shitong Wang:
Joint Learning of Spectral Clustering Structure and Fuzzy Similarity Matrix of Data. IEEE Trans. Fuzzy Syst. 27(1): 31-44 (2019) - [c287]Hisao Ishibuchi, Yiming Peng, Ke Shang:
A Scalable Multimodal Multiobjective Test Problem. CEC 2019: 310-317 - [c286]Yiping Liu, Hisao Ishibuchi, Yusuke Nojima, Naoki Masuyama, Yuyan Han:
Searching for Local Pareto Optimal Solutions: A Case Study on Polygon-Based Problems. CEC 2019: 896-903 - [c285]Kanzhen Wan, Cheng He, Auraham Camacho, Ke Shang, Ran Cheng, Hisao Ishibuchi:
A Hybrid Surrogate-Assisted Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization. CEC 2019: 2018-2025 - [c284]Hisao Ishibuchi, Linjun He, Ke Shang:
Regular Pareto Front Shape is not Realistic. CEC 2019: 2034-2041 - [c283]Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima, Hisao Ishibuchi:
A Multiobjective Test Suite with Hexagon Pareto Fronts and Various Feasible Regions. CEC 2019: 2058-2065 - [c282]Hisao Ishibuchi, Ryo Imada, Naoki Masuyama, Yusuke Nojima:
Two-Layered Weight Vector Specification in Decomposition-Based Multi-Objective Algorithms for Many-Objective Optimization Problems. CEC 2019: 2434-2441 - [c281]Auraham Camacho, Gregorio Toscano Pulido, Ricardo Landa Becerra, Hisao Ishibuchi:
Indicator-Based Weight Adaptation for Solving Many-Objective Optimization Problems. EMO 2019: 216-228 - [c280]Hisao Ishibuchi, Ryo Imada, Naoki Masuyama, Yusuke Nojima:
Comparison of Hypervolume, IGD and IGD+ from the Viewpoint of Optimal Distributions of Solutions. EMO 2019: 332-345 - [c279]Yusuke Nojima, Takafumi Fukase, Yiping Liu, Naoki Masuyama, Hisao Ishibuchi:
Constrained multiobjective distance minimization problems. GECCO 2019: 586-594 - [c278]Ryoji Tanabe, Hisao Ishibuchi:
Non-elitist evolutionary multi-objective optimizers revisited. GECCO 2019: 612-619 - [c277]Hisao Ishibuchi, Hiroyuki Sato:
Evolutionary many-objective optimization. GECCO (Companion) 2019: 614-661 - [c276]Weiyu Chen, Hisao Ishibuchi, Ke Shang:
Effects of Discretization of Decision and Objective Spaces on the Performance of Evolutionary Multi-objective Optimization Algorithms. SSCI 2019: 1826-1833 - [c275]Linjun He, Yang Nan, Ke Shang, Hisao Ishibuchi:
A Study of the Naïve Objective Space Normalization Method in MOEA/D. SSCI 2019: 1834-1840 - [c274]Weiduo Liao, Ke Shang, Lie Meng Pang, Hisao Ishibuchi:
Weak Convergence Detection-based Dynamic Reference Point Specification in SMS-EMOA. SSCI 2019: 1841-1848 - [c273]Hisao Ishibuchi, Takashi Matsumoto, Naoki Masuyama, Yusuke Nojima:
Optimal Distributions of Solutions for Hypervolume Maximization on Triangular and Inverted Triangular Pareto Fronts of Four-Objective Problems. SSCI 2019: 1857-1864 - [c272]Yiming Peng, Hisao Ishibuchi, Ke Shang:
Multi-modal Multi-objective Optimization: Problem Analysis and Case Studies. SSCI 2019: 1865-1872 - [c271]Mengjun Ming, Rui Wang, Tao Zhang, Hisao Ishibuchi:
A dual-grid dual-phase strategy for constrained multi-objective optimization. SSCI 2019: 1881-1888 - [c270]Lie Meng Pang, Hisao Ishibuchi, Ke Shang:
Offline Automatic Parameter Tuning of MOEA/D Using Genetic Algorithm. SSCI 2019: 1889-1897 - [c269]Naoki Masuyama, Narito Amako, Yusuke Nojima, Yiping Liu, Chu Kiong Loo, Hisao Ishibuchi:
Fast Topological Adaptive Resonance Theory Based on Correntropy Induced Metric. SSCI 2019: 2215-2221 - [c268]