Self-Organizing Maps
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
Niching and Elitist Models for MOGAs
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
Search Based Requirements Optimisation: Existing Work and Challenges
REFSQ '08 Proceedings of the 14th international conference on Requirements Engineering: Foundation for Software Quality
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Online Objective Reduction to Deal with Many-Objective Problems
EMO '09 Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization
A systems approach to evolutionary multiobjective structural optimization and beyond
IEEE Computational Intelligence Magazine
Heatmap visualization of population based multi objective algorithms
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Knowledge extraction from unstructured surface meshes
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
Automated innovization for simultaneous discovery of multiple rules in bi-objective problems
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
Visualizing 4D approximation sets of multiobjective optimizers with prosections
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Design knowledge extraction in multi-objective optimization problems
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Modeling design and flow feature interactions for automotive synthesis
IDEAL'11 Proceedings of the 12th international conference on Intelligent data engineering and automated learning
Neuroevolution with manifold learning for playing Mario
International Journal of Bio-Inspired Computation
High-Fidelity multidisciplinary design optimization of wing shape for regional jet aircraft
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
GECCO 2012 tutorial on evolutionary multiobjective optimization
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
GECCO 2013 tutorial on evolutionary multiobjective optimization
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Visualization and exploration of optimal variants in product line engineering
Proceedings of the 17th International Software Product Line Conference
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Self-Organizing Maps (SOMs) have been used to visualize tradeoffs of Pareto solutions in the objective function space for engineering design obtained by Evolutionary Computation. Furthermore, based on the codebook vectors of cluster-averaged values of respective design variables obtained from the SOM, the design variable space is mapped onto another SOM. The resulting SOM generates clusters of design variables, which indicate roles of the design variables for design improvements and tradeoffs. These processes can be considered as data mining of the engineering design. Data mining examples are given for supersonic wing design and supersonic wing-fuselage design.