A new multiobjective optimization with elliptical constraints approach for nonlinear models implemented in a stainless steel cladding process

A multiobjective optimization of the welding process in aluminum alloy (AA) 6063 T4 tubes used in corona rings through normal boundary intersection and multivariate techniques

“…This means that the variables vary concomitantly, and it is recommended to analyze them through simultaneous confidence intervals. A deeper explanation about this concept may be found in [13,42].…”

“…However, it is not a welding defect as it does not interfere in the construction of the corona ring. The analysis of the results followed mainly a recent methodology published in [13].…”

“…As previously discussed, this is the main raw material for manufacturing anti-corona protection rings, used by several companies in the electric energy segment during the assembly of medium and high voltage circuit breakers. Thus, this work proposes a new approach of the methodology developed in [13] for multiobjective optimization in the MIG welding process of corona rings, since the most important response had its range defined by the manager of the process what influenced in stablishing the range of the other correlated responses.…”

A multiobjective portfolio optimization for energy assets using D-Optimal design and mixture design of experiments

“…For instance, return, to be maximized and variability, to be minimized. In order to overcome this problem, the technique of Factor Mean Square Error (FMSE) proposed by (Leite, 2019) as a variation of Multivariate Mean Square Error (MMSE) developed in (Paiva et al, 2009) can be applied as in (Luz et al, 2021). Initially, the targets for the factors are calculated as shown in Equation 6, where i T is the target for the i th factor, Z is the vector of standardized variables, and i L is the vector of loadings composed of the correlations between the original variables and the ith factor.…”