Decision Support Systems
Models and tools that help people make well-informed decisions in complex, uncertain settings.
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Finding Sets of Pareto Sets in Real-World Scenarios – A Multitask Multiobjective Perspective
J Liu, YS Ong, M Wong. Cited by 3
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MEGO: Learning Mixture-of-Experts for General-Purpose Binary Optimization
S Liu, Z Wang, YS Ong, X Yao, T Ke
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PR-NeuS: A Prior-based Residual Learning Paradigm for Fast Multi-view Neural Surface Reconstruction
J Xu, Q Xu, X Liao, W Su, C Zhang, YS Ong, W Tao
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A Generalized and Configurable Benchmark Generator for Continuous Unconstrained Numerical Optimization
AH Gandomi, MN Omidvar, S Rohit, K Deb. Cited by 2
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GNBG-Generated Test Suite for Box-Constrained Numerical Global Optimization
AH Gandomi, D Yazdani, MN Omidvar, K Deb. Cited by 1
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Multi-objective evolutionary design of microstructures using diffusion autoencoders
A Suresh, D Shah, AS Admasu, D Upadhyay, K Deb. Cited by 1
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IK-EMOViz: An Interactive Knowledge-Based Evolutionary Multi-objective Optimization Framework
A Ghosh, K Deb, R Averill, E Goodman. Cited by 1
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A Comparative Study of Pareto Front of Optimal Solution Set for NAO Robot’s Gait Optimization Using the Dominance Move Indicator Based on Mixed Integer Programming
P Gupta, DK Pratihar, K Deb. Cited by 1
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On the choice of unique identifiers for predicting pareto-optimal solutions using machine learning
A Suresh, K Deb. Cited by 2
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Nested bilevel evolutionary algorithm (N-BLEA)
A Sinha, P Malo, K Deb. Cited by 2
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Inverse transfer multiobjective optimization
J Liu, A Gupta, YS Ong. Cited by 2
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An interview with kalyanmoy deb 2022 ACM fellow
K Deb. Cited by 3