In metropolitan cities an efficient integrated public transportation system is unavoidable to restrict unsustainable growth of private and intermediate transport modes. Well-designed feeder routes and coordinated schedules to minimize transfer time from the main transit to feeder buses play an important role. Past literature reveals that a heuristic approach had been popular for design of routes and had been applied successfully in a variety of network design problems. Nontraditional optimization techniques, especially genetic algorithms, are also found to be very effective in the generation of optimized feeder routes and schedules. In this research the genetic algorithm first develops feeder routes and then a specialized heuristic algorithm works as a repair algorithm to satisfy the demand of all the nodes. Thus, the advantages of both genetic algorithms and specialized heuristic algorithms are obtained in this method. The developed feeder route structure is found to be better in terms of load factors in buses, satisfaction of demand, and waiting time for feeder buses as compared to existing scenarios and earlier approaches adopted for the same study area.