This paper presents an improved Genetic Algorithm to solve the Transportation Network Design Problem (CTNDP) with interactions among different links. The CTNDP is formulated in an optimal design as a bi-level programming model. A key factor in the present approach is the combination of diploid based complex-encoding with meiosis specific features. The novel mutation operator proposed is another improvement that leads to a better robustness and convergence stability. The computational results obtained by comparing the performance of the proposed algorithm and other Genetic Algorithms for a test network demonstrates its better local searching ability, as well as its high efficiency. Finally, suggestions for further research and extensions are given.
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