IEEE Transactions on Magnetics · 1998 · 17 citations · 7 references
Natural SciencesIndustrial EngineeringMathematicsDesign OptimizationMulti-criteria Decision MakingOptimizationMulti-objective OptimizationMultiobjective OptimizationOptimization ModelingOptimization TheoryOptimization Under UncertaintyStochastic OptimizationBasis FunctionsCost Function ModelingFuzzy SetsMulti-objective Stochastic OptimizationRadial Basis Function NetworksRadial Basis Function SurrogatesStochastic Multi-criteria OptimizationStochastic Multiobjective Optimization
The present paper discusses a technique, based on the combined use of Radial Basis Functions (RBF), which provide an analytical approximation of the true cost function, and self adaptive fuzzy sets, which allow a flexible combination of conflicting objectives, for the stochastic optimisation of multiminima problems. The proposed technique is fully described, its features of interest for industrial level design optimisation are outlined and some initial positive results are presented.
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