Minima distribution for global optimization
Not on the map. Why?
Abstract (arXiv)
This paper establishes a strict mathematical relationship between an arbitrary continuous function on a compact set and its global minima, like the well-known first order optimality condition for convex and differentiable functions. By introducing a class of nascent minima distribution functions that is only related to the target function and the given compact set, we construct a sequence that monotonically converges to the global minima on that given compact set. Then, we further consider some various sequences of sets where each sequence monotonically shrinks from the original compact set to the set of all global minimizers, and the shrink rate can be determined for continuously differentiable functions. Finally, we provide a different way of constructing the nascent minima distribution functions.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Dec 2018.
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Citing papers per year: 2023: 1; 2024: 1.
2 papers.
- 2024Stein Boltzmann Sampling: A Variational Approach for Global Optimizationcited by 2
- 2023ProGO: Probabilistic Global Optimizercited by 0
- 2024Stein Boltzmann Sampling: A Variational Approach for Global Optimization7 Feb 2024
- 2023ProGO: Probabilistic Global Optimizer4 Oct 2023