Monte Carlo Simulation and Global Optimization without Parameters

Bobby Hesselbo and R. B. Stinchcombe
Phys. Rev. Lett. 74, 2151 – Published 20 March 1995
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Abstract

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 behavior (if present) without any parameter tuning. We test it on the traveling salesperson problem, the Edwards-Anderson spin glass, and the triangular antiferromagnet.

  • Received 31 May 1994

DOI:https://doi.org/10.1103/PhysRevLett.74.2151

©1995 American Physical Society

Authors & Affiliations

Bobby Hesselbo and R. B. Stinchcombe

  • Theoretical Physics, University of Oxford, 1 Keble Road, Oxford, OX1 3NP, United Kingdom

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Vol. 74, Iss. 12 — 20 March 1995

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