Manifold‐mapping (MM) is an efficient surrogate‐based optimization technique aimed at the acceleration of very time‐consuming design problems. In this paper we present two new variants of the original algorithm that make it applicable to a broader range of optimization scenarios.
The first variant is useful when the optimization constraints are expressed by means of functions that are very expensive to compute. The second variant endows the original scheme with a trust‐region strategy and the result is a much more robust algorithm.
Two practical optimization problems from electromagnetics eventually show that the proposed variants perform efficiently.
The original MM algorithm is extended with two new variants. Therefore, the MM approach is applicable to a much larger set of design situations.
