TRUST: A Deterministic Algorithm for Global Optimization

Abstract

An approach to solving continuous global optimization problems was developed. It builds on two innovative concepts, subenergy tunneling and non-Lipschitzian terminal repellers, to ensure escape from local minima in a fast, reliable, and computationally efficient manner. The generally applicable methodology is embodied in the TRUST (terminal repeller unconstrained subenergy tunneling) algorithm, which is deterministic, scalable, and easy to implement. Benchmark results show that TRUST is faster and more accurate than previously reported global optimization techniques. An application of TRUST to a large-scale exploratory seismology problem of substantial computational complexity (that is, residual statics corrections) is also reported.

Identification of Multilayered Particles from Scattering Data by a Clustering Method

“…[4], [6]. Among them are the simulated annealing method ( [20], [21]), various genetic algorithms [16], interval method, TRUST method ( [2], [3]), etc. As we have already mentioned before, the best fit to data functional Φ has many narrow local minima.…”

Constant-time solution to the global optimization problem using Br schweiler s ensemble search algorithm

“…Once that phase of the algorithm is reached, one can apply a scaling (dilation) transformation that maintains the descent mode but moderates the gradients. On the other hand, as one approaches the global minimum, the gradients become very small and certain acceleration techniques based on non-Lipschitzian dynamics may be required [18,19]. If the global minimum is attained at the boundary of the domain, the algorithm above will find it without additional complications.…”

Quantum Algorithm for Continuous Global Optimization

“…Once that phase of the algorithm is reached, one can proceed to apply a scaling (dilation) transformation that maintains the descent mode but moderates the gradients. On the other hand, as one approaches the global minimum, the gradients become very small and certain acceleration techniques based on non-Lipschitzian dynamics may be required [1,2]. If the global minimum is attained at the boundary of the domain, the algorithm above will nd it without additional complications.…”