@InProceedings{HernándezTorresCampChiw:2016:RoSaMP,
               author = "Hern{\'a}ndez Torres, Reynier and Campos Velho, Haroldo Fraga de 
                         and Chiwiacowsky, Leonardo Dagnino",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Rotation-based sampling MPCA-HJ for Vibration-based Damage 
                         Identification",
                 year = "2016",
         organization = "International Conference on Engineering Optimization, 5. 
                         (EngOpt)",
             abstract = "Multi-Particle Collision Algorithm (MPCA) is a stochatic 
                         optimization method inspired on the physics in the nuclear 
                         reactor, where absorption and scattering phenomena are 
                         represented. In the MPCA algorithm, a set of particles (solutions) 
                         travels in the search space. After a certain number of function 
                         evaluations, they share the best particle solution found. MPCA -- 
                         working together to the Rotation-Based Learning (RBL)-- is used as 
                         a first stage of the hybrid method performing a global exploratory 
                         search. RBL is a novel extension of Opposition-based Learning 
                         (OBL). In RBL, a rotated solution is calculated by applying a 
                         specific rotation angle to the original solution. Here, the new 
                         Rotation-Based Sampling (RBS) solution projects a point between 
                         the original solution and its rotated solution. RBS could be more 
                         flexible than RBL -- and also OBL -- to find the promising 
                         candidate solutions. The intensification search stage of the 
                         hybrid metaheuristic is addressed by the direct search 
                         Hooke-Jeeves (HJ) method. HJ consists of the repeatedly 
                         application of exploratory searches for all dimensions around a 
                         base point. If the exploration has success finding a better 
                         solution, a pattern move is performed. The hybrid algorithm is 
                         tested to identify damages over a truss structure. Experimental 
                         data was generated in silico, using time-invariant damages. 
                         Experiments with noiseless and noisy data, under several noise 
                         level, were carried out. Good estimations of damage location and 
                         severity are achieved.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "19-23 June",
             language = "en",
        urlaccessdate = "27 abr. 2024"
}