Decision Support Systems
Models and tools that help people make well-informed decisions in complex, uncertain settings.
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Ensemble Surrogate-Assisted Optimization with Dynamic Dimensional Splitting for High-Dimensional Expensive Mixed-Variable Problems
J Yi, S Zhu, M Cui, K Deb
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A Surrogate-Assisted Evolutionary Algorithm with Innovized Progress Operator for Expensive Many-Objective Optimization
X Yang, WH Fang, S Zhu, K Deb, M Cui
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Advances in Multi-Objective Optimization and Decision-Making
K Deb, D Yadav
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pMachine-DM: A Stochastic Machine Learning-Based Decision-Maker for Interactive Multi-Criterion Decision-Making
D Yadav, K Deb. Cited by 1
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GNBG-III: A Property-Aware Benchmark Suite for Diagnosing Continuous Black-Box Optimizers
R Salgotra, K Deb, AH Gandomi. Cited by 1
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To Balance Competitive Games Using a Multi-objective Coevolutionary Approach
S Raj, A Garrard, R Mckendrick, B Feest, K Deb
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Benchmarking Interactive Multi-Criterion Decision-Making Procedures Following Machine Learning-Based Decision-Maker
D Yadav, K Deb. Cited by 1
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Following natural evolution closely in devising evolutionary algorithms for certain challenging problems
A Khan, K Deb
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Orthogonal Meta-learning Boosted Bayesian Optimization for Uncertain Multi-Objective Recommendation
H Wang, Y Du, Z Sun, L Zhang, T He, YS Ong. Cited by 1
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Artificial Intelligence, Optimization, and Modeling Techniques in Water Resources Management: Challenges and Future Directions
HS Razavi, AP Nejadhashemi, K Deb, G Toscano‐Pulido, T Harrigan, LC Linker. Cited by 1
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Population versus point-based optimization algorithms for hierarchical convergence to multiple solutions
A Khan, K Deb
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MToP: A MATLAB Benchmarking Platform for Evolutionary Multitasking
Y Li, W Gong, T Zhang, F Ming, S Li, Q Gu, YS Ong. Cited by 2