The single row facility layout is the NP-Hard problem of arranging facilities with given lengths on a line, so as to minimize the weighted sum of the distances between all pairs of facilities. Owing to the computational complexity of the problem, researchers have developed several heuristics to obtain good quality solutions. In this paper, we present a genetic algorithm to solve large SRFLP instances. Our computational experiments show that an appropriate selection of genetic operators can yield high quality solutions in spite of starting with an initial population that is largely randomly generated. Our algorithm improves the previously best known solutions for the 24 instances of 43 benchmark instances and is competitive for the remaining ones.