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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.
