Simulated annealing with time-dependent energy function via Sobolev inequalities

DOI10.1016/0304-4149(96)00070-1zbMath0910.60060OpenAlexW2052038516MaRDI QIDQ1272167

Matthias Loewe

Publication date: 23 November 1998

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4149(96)00070-1

zbMATH Keywords

simulated annealingspectral gapSobolev inequalities

Mathematics Subject Classification ID

Continuous-time Markov processes on discrete state spaces (60J27) Applications of queueing theory (congestion, allocation, storage, traffic, etc.) (60K30)

Related Items

An adaptive simulated annealing algorithm. ⋮ Some remarks on replicated simulated annealing ⋮ On the invariant measure of non-reversible simulated annealing ⋮ From simulated annealing to stochastic continuation: a new trend in combinatorial optimization ⋮ On simulated annealing with temperature-dependent energy and temperature-dependent communication ⋮ Stochastic protein folding simulation in the three-dimensional HP-model ⋮ Stochastic gradient descent and fast relaxation to thermodynamic equilibrium: A stochastic control approach

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Optimization by Simulated Annealing
• Eigenvalue bounds on convergence to stationarity for nonreversible Markov chains, with an application to the exclusion process
• Geometric bounds for eigenvalues of Markov chains
• Nonstationary Markov chains and convergence of the annealing algorithm
• Simulated annealing via Sobolev inequalities
• Sharp large deviations estimates for simulated annealing algorithms
• Applied simulated annealing
• Simulated annealing with time-dependent energy function
• \(L^ 2\) convergence of time nonhomogeneous Markov processes. I: Spectral estimates
• On the convergence of genetic algorithms
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Matrix Analysis
• Cooling Schedules for Optimal Annealing
• Neural networks and physical systems with emergent collective computational abilities.