Landscape analysis for multicast routing
Computer Communications
Genetic local search for multicast routing with pre-processing by logarithmic simulated annealing
Computers and Operations Research
Stochastic protein folding simulation in the three-dimensional HP-model
Computational Biology and Chemistry
Stochastic protein folding simulation in the d-dimensional HP-model
BIRD'07 Proceedings of the 1st international conference on Bioinformatics research and development
Landscape analysis for protein-folding simulation in the h-p model
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
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We perform a convergence analysis of simulated annealing-based search for the special case of logarithmic cooling schedules. Emphasis is put on the impact of structural parameters of the underlying configuration space on the number of transitions k≥L that is sufficient to achieve a certain probability (confidence 1−δ) of being in an optimum configuration. Since such a lower bound L of the transition number depends on some constants that are difficult to calculate, we evaluate a much simplified version L'≪L of the lower bound for the problem of finding short conjunctions representing a ``positive'' Boolean vector and rejecting a set of ``negative'' Boolean vectors. The evaluation is based on computational experiments where the frequency of occurrences of configurations is calculated for simulated annealing-based search that terminates after L' transitions. The experiments produce a good correspondence between frequencies of minimum configurations and the required confidence 1−δ, i.e., our study provides empirical evidence that the relation of basic parameters in the lower bound L, if calculated for small constants assigned to the parameters and thus resulting in L', can be used as a termination criterion in simulated annealing-based search.