Decision Support Systems
Models and tools that help people make well-informed decisions in complex, uncertain settings.
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I-MODE: An Interactive Multi-objective Optimization and Decision-Making Using Evolutionary Methods
K Deb, S Chaudhuri. Cited by 48
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Reliability-Based Multi-objective Optimization Using Evolutionary Algorithms
K Deb, D Padmanabhan, S Gupta, AK Mall. Cited by 55
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Non-linear Dimensionality Reduction Procedures for Certain Large-Dimensional Multi-objective Optimization Problems: Employing Correntropy and a Novel Maximum Variance Unfolding
DK Saxena, K Deb. Cited by 116
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Dynamic Multi-objective Optimization and Decision-Making Using Modified NSGA-II: A Case Study on Hydro-thermal Power Scheduling
K Deb, UBR N., S Karthik. Cited by 561
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Evolutionary Multi-Objective Optimization Without Additional Parameters
K Deb. Cited by 11
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Evolutionary Computation in Dynamic and Uncertain Environments (Studies in Computational Intelligence)
S Yang, YS Ong, Y Jin. Cited by 17
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An Adaptive Multimeme Algorithm for Designing HIV Multidrug Therapies
F Neri, J Toivanen, GL Cascella, YS Ong. Cited by 120
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Markov blanket-embedded genetic algorithm for gene selection
Z Zhu, YS Ong, M Dash. Cited by 501
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Wrapper–Filter Feature Selection Algorithm Using a Memetic Framework
Z Zhu, YS Ong, M Dash. Cited by 443
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Evolvable Fuzzy Scheduling Scheme for Multiple-ChannelPacket Switching Network
JH Li, MH Lim, YS Ong, QP Cao
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A Study on Metamodeling Techniques, Ensembles, and Multi-Surrogates in Surrogate-Assisted Memetic Algorithms
D Lim, YS Ong, Y Jin, B Sendhoff. Cited by 4
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Single/Multi-objective Inverse Robust Evolutionary Design Methodology in the Presence of Uncertainty
D Lim, YS Ong, M Lim, Y Jin. Cited by 21