Mass transit route network design using genetic algorithm

The mass transit route network design (MTRND) problem is a bi‐level NP‐hard problem and difficult to solve for a global optimum solution. This paper proposes a genetic algorithm for solving the MTRND problem. In the proposed algorithm, two smart generating methodologies are formulated to achieve a better searching space for the initial feasible solution. An efficient network model, a gene repairing strategy and a redundancy checking mechanism were applied to minimize the computation time. Improved fitness function was embedded with the passenger assignment model and utilized to improve the quality of the solution. The proper combination of crossover operators and mutation operators was found for the MTRND. The proposed algorithm was tested with the current MRT network in Taipei as a specimen. Results indicate that the proposed algorithm is effective in solving real‐world problems.