Pathwise recurrence orders and simulated annealing

1992 ◽  
Vol 29 (2) ◽  
pp. 472-476 ◽  
Author(s):  
Vivek S. Borkar
Keyword(s):  
Simulated Annealing ◽  
Markov Chains ◽  
Path Analysis ◽  
Simulated Annealing Algorithm ◽  
Sample Path ◽  
State Transitions ◽  
Sample Path Analysis ◽  
Annealing Algorithm

The Connors–Kumar notion of recurrence orders for state and state transitions of time-inhomogeneous Markov chains is redefined ‘pathwise' and applied to the sample path analysis of the simulated annealing algorithm.

Pathwise recurrence orders and simulated annealing

1992 ◽  
Vol 29 (02) ◽  
pp. 472-476 ◽  
Author(s):  
Vivek S. Borkar
Keyword(s):  
Simulated Annealing ◽  
Markov Chains ◽  
Path Analysis ◽  
Simulated Annealing Algorithm ◽  
Sample Path ◽  
State Transitions ◽  
Sample Path Analysis ◽  
Annealing Algorithm

The Connors–Kumar notion of recurrence orders for state and state transitions of time-inhomogeneous Markov chains is redefined ‘pathwise' and applied to the sample path analysis of the simulated annealing algorithm.

Tail events of simulated annealing Markov chains

1995 ◽  
Vol 32 (4) ◽  
pp. 867-876 ◽  
Author(s):  
Wojciech Niemiro
Keyword(s):  
Simulated Annealing ◽  
Markov Chains ◽  
Simulated Annealing Algorithm ◽  
Asymptotic Properties ◽  
Transient States ◽  
Annealing Algorithm ◽  
Tail Events

We consider non-homogeneous Markov chains generated by the simulated annealing algorithm. We classify states according to asymptotic properties of trajectories. We identify recurrent and transient states. The set of recurrent states is partitioned into disjoint classes of asymptotically communicating states. These classes correspond to atoms of the tail sigma-field. The results are valid under the weak reversibility assumption of Hajek.

Tail events of simulated annealing Markov chains

1995 ◽  
Vol 32 (04) ◽  
pp. 867-876 ◽  
Author(s):  
Wojciech Niemiro
Keyword(s):  
Simulated Annealing ◽  
Markov Chains ◽  
Simulated Annealing Algorithm ◽  
Asymptotic Properties ◽  
Transient States ◽  
Annealing Algorithm ◽  
Tail Events

We consider non-homogeneous Markov chains generated by the simulated annealing algorithm. We classify states according to asymptotic properties of trajectories. We identify recurrent and transient states. The set of recurrent states is partitioned into disjoint classes of asymptotically communicating states. These classes correspond to atoms of the tail sigma-field. The results are valid under the weak reversibility assumption of Hajek.

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