In this paper, the authors propose a new model showing how genetic algorithms (GAs) can be manipulated to help optimize bus transit routing design, incorporating unique service frequency settings for each route. The main lesson is in the power that can be given to heuristic methods if problem content is exploited appropriately. In this example, 7 proposed genetic operators are designed for this specific problem to facilitate a search within a reasonable amount of time. In addition, headway coordination is applied by ranking of transfer demands at the transfer terminals. The model is applied on a benchmark network to test its efficiency, and performance results are presented. It is shown that the proposed model is more efficient than the binary-coded GA benchmark, in which problem content cannot be utilized.
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