TRUST REGION Meaning and
Definition
-
Trust region is a term used in optimization and numerical analysis that refers to a region within which certain characteristics of an iteratively-improved solution are trusted to hold true. It is typically used in the context of solving nonlinear optimization problems, where the objective is to find the optimal solution that minimizes or maximizes a given function while satisfying certain constraints.
In practical terms, a trust region defines a region around the current estimate of the solution that can be trusted to yield a good approximation to the true solution. This region is typically defined by a geometric shape, such as a ball or an ellipsoid, and is centered at the current estimate. The size of the trust region is typically iteratively-adjusted based on the progress of the optimization algorithm, aiming to strike a balance between exploration of the solution space and convergence towards the optimal solution.
The main purpose of using a trust region is to ensure that the optimization algorithm remains within a region where certain assumptions about the function, such as smoothness or convexity, hold true. By restricting the search within this region, the algorithm can make more informed decisions about the direction to proceed, avoiding unnecessary exploration of irrelevant or uncertain parts of the solution space. This allows for more efficient and effective convergence towards the optimal solution.
Overall, the concept of a trust region provides a systematic approach to controlling the behavior of optimization algorithms, enabling them to balance exploration and exploitation to efficiently converge towards an optimal solution.
Etymology of TRUST REGION
The term "trust region" has its roots in mathematical optimization and was coined by Moré and Sorensen in the late 1970s. In optimization, a "trust region" is a region around the current point in the search space where the objective function is believed to have a good approximation. The idea is to find an optimal solution within this trust region without exploring the entire search space, which can be computationally expensive. The term "trust" refers to the confidence placed in the accuracy of the approximation within the region. The concept of trust regions has since been applied in various fields, including machine learning and computer vision, to solve optimization problems efficiently.
