Optimization and benchmarking of the thermal cycling algorithm

• URL: http://arxiv.org/abs/2012.09801v2
• Date: Wed, 8 Sep 2021 15:40:46 GMT
• Title: Optimization and benchmarking of the thermal cycling algorithm
• Authors: Amin Barzegar, Anuj Kankani, Salvatore Mandr\`a, Helmut G. Katzgraber
• Abstract summary: Most of the optimization problems have inordinately complex structures that render finding their daunting task. In this paper we benchmark and improve an algorithm that is designed to overcome energy barriers in non optimization problems by temperature. We demonstrate that it competes closely with other state-of-the-art algorithms such as parallel cycling with isoenergetic moves.
• Score: 0.5879782260984691
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Optimization plays a significant role in many areas of science and technology. Most of the industrial optimization problems have inordinately complex structures that render finding their global minima a daunting task. Therefore, designing heuristics that can efficiently solve such problems is of utmost importance. In this paper we benchmark and improve the thermal cycling algorithm [Phys. Rev. Lett. 79, 4297 (1997)] that is designed to overcome energy barriers in nonconvex optimization problems by temperature cycling of a pool of candidate solutions. We perform a comprehensive parameter tuning of the algorithm and demonstrate that it competes closely with other state-of-the-art algorithms such as parallel tempering with isoenergetic cluster moves, while overwhelmingly outperforming more simplistic heuristics such as simulated annealing.

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