Monte Carlo simulation and global optimization without parameters

Details Monte Carlo simulation and global optimization without parameters Monte Carlo simulation and global optimization without parameters

1995-01-24

arxiv.org/abs/cond-mat/9501114v1

Phys. Rev. Lett. 74 (1995) 2151

Physics

Condensed Matter

10 pages with 3 Postscript figures, to appear in Phys. Rev. Lett.

Scientific paper

10.1103/PhysRevLett.74.2151

We propose a new ensemble for Monte Carlo simulations, in which each state is assigned a statistical weight $1/k$, where $k$ is the number of states with smaller or equal energy. This ensemble has robust ergodicity properties and gives significant weight to the ground state, making it effective for hard optimization problems. It can be used to find free energies at all temperatures and picks up aspects of critical behaviour (if present) without any parameter tuning. We test it on the travelling salesperson problem, the Edwards-Anderson spin glass and the triangular antiferromagnet.

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