Optimizing at the Ergodic Edge
计算物理
2018-07-06 v1 无序系统与神经网络
综合物理
摘要
Using a simple, annealed model, some of the key features of the recently introduced extremal optimization heuristic are demonstrated. In particular, it is shown that the dynamics of local search possesses a generic critical point under the variation of its sole parameter, separating phases of too greedy (non-ergodic, jammed) and too random (ergodic) exploration. Comparison of various local search methods within this model suggests that the existence of the critical point is essential for the optimal performance of the heuristic.
引用
@article{arxiv.physics/0509001,
title = {Optimizing at the Ergodic Edge},
author = {Stefan Boettcher and Martin Frank},
journal= {arXiv preprint arXiv:physics/0509001},
year = {2018}
}
备注
RevTex4, 17 pages, 3 ps-figures incl., for related information, see http://www.physics.emory.edu/faculty/boettcher/publications.html