We develop a genetic algorithm for the topological design of survivable optical transport networks with minimum capital expenditure. Using the developed genetic algorithm we can obtain near-optimal topologies in a short time. The quality of the obtained solutions is assessed using an integer linear programming model. Two initial population generators, two selection methods, two crossover operators, and two population sizes are analyzed. Computational results obtained using real telecommunications networks show that by using an initial population that resembles real optical transport networks a good convergence is achieved.