A Genetic Approximation of Closest String via Rank Distance

This paper aims to fully present a new genetic approach that uses rank distance for solving two known NP-complete problems: closest string and closest substring. We build a genetic algorithm for each of the two problems and we describe the genetic operations involved. The genetic algorithm adapted for the closest substring problem uses standard genetic operations, while the genetic operations for the closest string problem are only inspired from nature. Both genetic algorithms bring something new by using a fitness function based on rank distance. The tests for both problems show that our genetic approach via rank distance has good results.