Decision Support Systems
Models and tools that help people make well-informed decisions in complex, uncertain settings.
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Emerging Techniques for Evolutionary Single- and Multi-objective Optimization with Application to Humanoid Robot Gait Generation
P Gupta, DK Pratihar, K Deb
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Evolutionary Multi and Many-Objective Optimization: Enhancements Using Machine Learning
DK Saxena, S Mittal, K Deb
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A Review on Bilevel Optimization Using Evolutionary Algorithms and Machine Learning Approaches
D Chauhan, H Ishibuchi, K Deb, A Trivedi, D Srinivasan
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Iteration-wise Intermediate Points Saved in an Archive as Outcome of an OptimizationAlgorithm Considered Unreliable
K Deb, A Khan
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A Fast Dominance Move Calculation Using Mixed-Integer Programming for Many-objective Optimization
CLDV Lopes, FVC Martins, EF Wanner, K Deb
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Handling of objectives and constraints with heterogeneous evaluation times for surrogate-assisted evolutionary multi- and many-objective optimization
B Santoshkumar, K Deb. Cited by 2
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Confound from all Sides, Distill with Resilience: Multi-Objective Adversarial Paths to Zero-Shot Robustness
J Dong, J Liu, X Qu, YS Ong. Cited by 1
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Evolutionary Computation as Natural Generative AI
S Yaxin, A Gupta, CW Wu, M Wong, IWH Tsang, T Rios, S Menzel, B Sendhoff, Y Hou, YS Ong
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A continuous encoding-based representation for efficient multi-fidelity multi-objective neural architecture search
Z Wei, CC Ooi, YS Ong
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A cooperative co-evolutionary algorithm with core-based grouping strategy for large-scale 0–1 knapsack problems
X Li, S Zhu, WH Fang, K Deb. Cited by 1
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Grounding Open-Domain Knowledge from LLMs to Real-World Reinforcement Learning Tasks: A Survey
H Yin, H Qian, Y Shi, IWH Tsang, YS Ong. Cited by 1
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Improved decisions for unknown behaviours in interactive dynamic influence diagrams
Y Pan, M Zhou, B Ma, Y Zeng, YS Ong, G Liu