Decision Support Systems
Models and tools that help people make well-informed decisions in complex, uncertain settings.
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GNBG: a generalized and configurable benchmark generator for continuous numerical optimization
D Yazdani, MN Omidvar, D Yazdani, K Deb, AH Gandomi. Cited by 10
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An interactive knowledge-based multiobjective evolutionary algorithm framework for practical optimization problems
A Ghosh, K Deb, E Goodman, R Averill. Cited by 11
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Finding robust solutions for many-objective optimization using NSGA-III
D Yadav, P Ramu, K Deb. Cited by 11
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A hybrid evolutionary cnn-lstm model for prognostics of c-mapss aircraft dataset
P Khumprom, A Davila-Frias, D Grewell, D Buakum. Cited by 11
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Pure and mixed lexicographic-paretian many-objective optimization: state of the art
L Lai, L Fiaschi, M Cococcioni, K Deb. Cited by 20
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Pareto optimization with small data by learning across common objective spaces
CS Tan, A Gupta, YS Ong, M Pratama, PS Tan, SK Lam. Cited by 19
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Key issues in real-world applications of many-objective optimisation and decision analysis
K Deb, P Fleming, Y Jin, K Miettinen, PM Reed. Cited by 13
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Evolutionary multi-task optimization
L Feng, A Gupta, KC Tan, YS Ong. Cited by 13
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A general framework for enhancing relaxed Pareto dominance methods in evolutionary many-objective optimization
S Zhu, L Xu, E Goodman, K Deb, Z Lu. Cited by 16
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Identifying pareto fronts reliably using a multistage reference-vector-based framework
K Deb, CL do Val Lopes, FVC Martins, EF Wanner. Cited by 17
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A user-guided innovization-based evolutionary algorithm framework for practical multi-objective optimization problems
A Ghosh, K Deb, E Goodman, R Averill. Cited by 15
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On generalized dominance structures for multi-objective optimization
K Deb, M Ehrgott. Cited by 16