Monte Carlo simulations global optimization

Hesselbo, B. Stinchcombe, R.B., Monte-Carlo simulation and global optimization without parameters, Phys. Rev. Lett. 1995, 74, 2151-2155... 

Compared to the other two approaches, deterministic optimization based on point estimates is by far the easiest approach. In this case the optimization is done once and for all before the Monte Carlo simulations. The disadvantage, however, is that this approach does not guarantee a globally optimal solution. 

To address the docking problem, techniques for a more global exploration of the en-ag/ landscape are required. A variety of methods is available, frequently used in the context cf other modeling applications and optimization problems as well. Three major classes may be distinguished Monte Carlo techniques, molecular dynamics simulations, and genetic algorithms. Many different vari-fants exist for all of them and frequently, in... 

However, there is no unique or optimal measure of accuracy. If MD simulations are performed, the main interest lies in errors connected with the force, while in Monte Carlo (MC) simulations one is concerned with accurate energies. In the simulation of ensemble averages it is the global accuracy, measured, e.g., by root-mean-square quantities, which is important, hi the simulation of rare events local accuracy and maximal errors are relevant as well. Errors in the force can be due to their magnitude or due to their direction. And finally, one might be interested in absolute or relative errors. 

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