Genetic Algorithms, Operators, and Dna Fragment Assembly Machine Learning { to Appear

We study diierent genetic algorithm operatorsfor one permutationproblem associated with the Human Genome Project|the assembly of DNA sequence fragments from a parent clone whose sequence is unknown into a consensus sequence corresponding to the parent sequence. The sorted-order representation, which does not require specialized operators, is compared with a more traditional permutation representation, which does require specialized operators. The two representations and their associated operators are compared on problems ranging from 2K to 34K base pairs (KB). Edge-recombination crossover used in conjunction with several specialized operators is found to perform best in these experiments; these operators solved a 10KB sequence, consisting of 177 fragments, with no manual intervention. Natural building blocks in the problem are exploited at progressivelyhigher levels through \macro-operators." This signiicantlyimproves performance.