But this creates another problem. As there is no general theory known for the proper weighting of each fitness component the only way is to try different combinations of values and evaluate them by their performance of a genetic algorithm on test proteins with known conformations. However, even for a small number of fitness components a large number of combinations of weights arises which requires as many test runs for evaluation. Also, expensive fitness components as the van der Waals energy need considerable computation time. This means that each fitness component is individually carried along the whole evaluation process and is always available explicitly.
Parallel processing is employed to evaluate all individuals of one generation in parallel.
In this application two versions of a fitness function are used. One version is a scalar fitness function that calculates the r.m.s.-deviation of a newly generated individual from the known conformation of the test protein. This geometric measure should guide the genetic algorithm directly to the desired solution but it is only available for proteins with a known conformation. The squares of the distances between the vectors u and v of corresponding atoms are summed and the square root is taken. The result is a measure of how much each atom in the individual deviates on average from its true position.