Changes

<math>\ln{P(X_n \not\in Cost_{min})} = \alpha \ln{K} - \alpha \ln{n}</math>

<math>\ln{P(X_n \not\in Cost_{min})} = \alpha \ln{K} - \alpha \ln{n}</math>

Once a sufficient number of runs have been completed, the &alpha; and ''K'' factors will be known and can thereby be exploited to find the most efficient chain length to run multiple independent Markov chains.

Once a sufficient number of runs have been completed, the &alpha; and ''K'' factors will be known and can thereby be exploited to find the most effective chain length to run multiple independent Markov chains. Given the potential size of the search space, one can

==References==

==References==