Automated Innovization for Simultaneous Discovery of Multiple Rules in Engineering Problems
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[1] Daisuke Sasaki,et al. Visualization and Data Mining of Pareto Solutions Using Self-Organizing Map , 2003, EMO.
[2] Eckart Zitzler,et al. Pattern identification in pareto-set approximations , 2008, GECCO '08.
[3] Akira Oyama,et al. Data Mining of Pareto-Optimal Transonic Airfoil Shapes Using Proper Orthogonal Decomposition , 2009 .
[4] K. Deb. An Efficient Constraint Handling Method for Genetic Algorithms , 2000 .
[5] Kalyanmoy Deb. MONOTONICITY ANALYSIS, EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION, AND DISCOVERY OF DESIGN PRINCIPLES , 2006 .
[6] Shigeru Obayashi,et al. Multi-Objective Design Exploration for Aerodynamic Configurations , 2005 .
[7] Kalyanmoy Deb,et al. Multi-objective Evolutionary Algorithms for Resource Allocation Problems , 2007, EMO.
[8] R. K. Ursem. Multi-objective Optimization using Evolutionary Algorithms , 2009 .
[9] Kalyanmoy Deb,et al. Towards automating the discovery of certain innovative design principles through a clustering-based optimization technique , 2011 .
[10] Henri Ruotsalainen,et al. New visualization aspects related to intelligent solution procedure in papermaking optimization , 2008 .
[11] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..
[12] Stéphane Doncieux,et al. Exploring new horizons in evolutionary design of robots , 2009 .
[13] Kalyanmoy Deb,et al. Automated discovery of vital knowledge from Pareto-optimal solutions: First results from engineering design , 2010, IEEE Congress on Evolutionary Computation.
[14] Kalyanmoy Deb,et al. Unveiling innovative design principles by means of multiple conflicting objectives , 2003 .
[15] Aravind Srinivasan,et al. Innovization: innovating design principles through optimization , 2006, GECCO.