Decision Support Systems
Models and tools that help people make well-informed decisions in complex, uncertain settings.
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Higher-level innovization: A case study from Friction Stir Welding process optimization
S Bandaru, CC Tutum, K Deb, JH Hattel. Cited by 12
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Modified SBX and adaptive mutation for real world single objective optimization
S Bandaru, R Tulshyan, K Deb. Cited by 32
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Multimodal Optimization Using a Bi-Objective Evolutionary Algorithm
K Deb, AK Saha. Cited by 123
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Optimization of the size of a solar thermal electricity plant by means of genetic algorithms
JM Cabello, JMC López, M Luque, F Ruiz, K Deb, R Tewari. Cited by 57
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Investigating the Role of Nonmetallic Fillers in Particulate-Reinforced Mold Composites using EAs
AK Nandi, S Datta, K Deb. Cited by 7
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Neural meta-memes framework for managing search algorithms in combinatorial optimization
LQ Song, MH Lim, YS Ong. Cited by 4
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Understanding knee points in bicriteria problems and their implications as preferred solution principles
K Deb, S Gupta. Cited by 297
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Improving convergence of evolutionary multi-objective optimization with local search: a concurrent-hybrid algorithm
K Sindhya, K Deb, K Miettinen. Cited by 37
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Towards automating the discovery of certain innovative design principles through a clustering-based optimization technique
S Bandaru, K Deb. Cited by 67
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CMAP
X Xin, MRT Lyu, I King. Cited by 3
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Toward an Evolutionary Computing Modeling Language
H Aydt, SJ Turner, W Cai, MYH Low, YS Ong, R Ayani. Cited by 7
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Asymmetric Pareto-adaptive Scheme for Multiobjective Optimization
S Jiang, J Zhang, YS Ong. Cited by 21