A Comparison of Extremal Optimization with Flat-Histogram and Equal-Hit Dynamics for Finding Spin–Glass Ground States
Jian-Sheng Wang,Yutaka Okabe +1 more
TLDR
In this article, the performance of extremal optimization (EO), flat-histogram and equal-hit algorithms for finding spin-glass ground states is compared, and the first-passage times to a ground state are computed.Abstract:
We compare the performance of extremal optimization (EO), flat-histogram and equal-hit algorithms for finding spin–glass ground states. The first-passage-times to a ground state are computed. At optimal parameter of τ=1.15, EO outperforms other methods for small system sizes, but equal-hit algorithm is competitive to EO, particularly for large systems. Flat-histogram and equal-hit algorithms offer additional advantage that they can be used for equilibrium thermodynamic calculations. We also propose a method to turn EO into a useful algorithm for equilibrium calculations.read more
Citations
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Wang-Landau sampling with self-adaptive range
TL;DR: A self-adapting version of the Wang-Landau algorithm that is ideally suited for application to systems with a complicated structure of the density of states and high-precision numerical integration of sharply peaked functions on multidimensional integration domains is reported.
Proceedings ArticleDOI
Survey on computational complexity with phase transitions and extremal optimization
Guo-Qiang Zeng,Yong-Zai Lu +1 more
TL;DR: This survey reviews the latest research results from fundamental to practice about the connection between computational complexity and phase transitions, and introduces the concepts, fundamentals, algorithms and applications of extremal optimization from its capability of self-organized criticality, backbone analysis and co-evolution moving to a far-from-equilibrium state.
Journal ArticleDOI
Optimizing at the ergodic edge
Stefan Boettcher,Martin Frank +1 more
TL;DR: Using a simple, annealed model, some of the key features of the recently introduced extremal optimization heuristic are demonstrated and it is shown that the dynamics of local search possesses a generic critical point under the variation of its sole parameter.
Book ChapterDOI
Evolutionary Dynamics of Extremal Optimization
TL;DR: In this paper, the authors analyzed the extremal optimization heuristic and showed that it performs optimally at a transition between a jammed and an diffusive state, where the existence of the critical point is the essential distinction leading to the optimal performance.
Proceedings Article
Evolutionary dynamics of extremal optimization
TL;DR: In this paper, the authors analyzed the extremal optimization heuristic and showed that it performs optimally at a transition between a jammed and an diffusive state, where the existence of the critical point is the essential distinction leading to the optimal performance.
References
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