AbstractWe analyze the simulated annealing algorithm with an energy function Ut that depends on time. Assuming some regularity conditions on Ut (especially that Ut does not change too quickly in time), and choosing a logarithmic cooling schedule for the algorithm, we derive bounds on the Radon-Nikodym density of the distribution of the annealing algorithm at time t with respect to the invariant measure πt at time t. Moreover, we estimate the entrance time of the algorithm into typical subsets V of the state space in terms of πt(Vc)
The aim of the present study is to elucidate how simulated annealing (SA) works in its finite-time i...
Simulated annealing is a probabilistic optimization algorithm which is used for approximating the gl...
Simulated annealing is a probabilistic algorithm for minimizing a general cost function which may ha...
AbstractWe analyze the simulated annealing algorithm with an energy function Ut that depends on time...
AbstractIn this paper, we compare from the theoretical and experimental points of view three stochas...
Bibliography: p. 16-17.Research supported by the Army Research Office under contract DAAAG-29-84-K-0...
We provide a set of conditions which ensure the almost sure convergence of a class of simulated anne...
"August 20, 1985."Bibliography: p. 32."U.S. Army Res. Off. ... Grant DAAG29-84-K-0005" "Air Force Of...
AbstractIn this paper we establish a weak and a strong law of large numbers for the algorithm of sim...
Simulated Annealing has proven to be a very sucessful heuristic for various combinatorial optimizati...
AbstractWe determine the optimal ensemble size for a simulated annealing problem based on assumption...
The convergence of the kinetic Langevin simulated annealing is proven under mild assumptions on the ...
Given an energy potential on the Euclidian space, a piecewise deterministic Markov process is design...
We present a new theoretical framework for analyzing simulated annealing. The behavior of simulated ...
The Digital Annealer is a CMOS hardware designed by Fujitsu Laboratories for high-speed solving of Q...
The aim of the present study is to elucidate how simulated annealing (SA) works in its finite-time i...
Simulated annealing is a probabilistic optimization algorithm which is used for approximating the gl...
Simulated annealing is a probabilistic algorithm for minimizing a general cost function which may ha...
AbstractWe analyze the simulated annealing algorithm with an energy function Ut that depends on time...
AbstractIn this paper, we compare from the theoretical and experimental points of view three stochas...
Bibliography: p. 16-17.Research supported by the Army Research Office under contract DAAAG-29-84-K-0...
We provide a set of conditions which ensure the almost sure convergence of a class of simulated anne...
"August 20, 1985."Bibliography: p. 32."U.S. Army Res. Off. ... Grant DAAG29-84-K-0005" "Air Force Of...
AbstractIn this paper we establish a weak and a strong law of large numbers for the algorithm of sim...
Simulated Annealing has proven to be a very sucessful heuristic for various combinatorial optimizati...
AbstractWe determine the optimal ensemble size for a simulated annealing problem based on assumption...
The convergence of the kinetic Langevin simulated annealing is proven under mild assumptions on the ...
Given an energy potential on the Euclidian space, a piecewise deterministic Markov process is design...
We present a new theoretical framework for analyzing simulated annealing. The behavior of simulated ...
The Digital Annealer is a CMOS hardware designed by Fujitsu Laboratories for high-speed solving of Q...
The aim of the present study is to elucidate how simulated annealing (SA) works in its finite-time i...
Simulated annealing is a probabilistic optimization algorithm which is used for approximating the gl...
Simulated annealing is a probabilistic algorithm for minimizing a general cost function which may ha...