Simulated annealing with hit-and-run for convex optimization: rigorous complexity analysis and practical perspectives for copositive programming

Riley Badenbroek; Etienne de Klerk

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arXiv · 1907.02368

Simulated annealing with hit-and-run for convex optimization: rigorous complexity analysis and practical perspectives for copositive programming

Riley Badenbroek·Etienne de Klerk

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Abstract

We give a rigorous complexity analysis of the simulated annealing algorithm by Kalai and Vempala [Math of OR 31.2 (2006): 253-266] using the type of temperature update suggested by Abernethy and Hazan [arXiv 1507.02528v2, 2015]. The algorithm only assumes a membership oracle of the feasible set, and we prove that it returns a solution in polynomial time which is near-optimal with high probability. Moreover, we propose a number of modifications to improve the practical performance of this method, and present some numerical results for test problems from copositive programming.

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BibTeX RIS

Riley Badenbroek, Etienne de Klerk. 2019-07-04. Simulated annealing with hit-and-run for convex optimization: rigorous complexity analysis and practical perspectives for copositive programming. https://arxiv.org/abs/1907.02368

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