MULTI-DEMSIONAL INTERGRATED TRANSPORT POLICIES OPTIMIZATION BASED ON GENETIC ALGORITHM AND REVISION REPORT

概要

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Empirical experiences showed that improving the urban transport problems should rely on integrated multi-dimensional transport policies which can also soften the demand of infrastructure investment. However, to fully consider the multi-dimensional transport polices in transportation planning framework would be very difficult due to the factor that there would be too many possible policy combinations to be evaluated. Therefore, this study attempts to develop an analytic framework for evaluating urban integrated transport policies comprehensively, including strategies of investment, pricing, management and regulation. In particular, to deal with the difficulty of too many policy combinations, genetic algorithms will be employed to search for the optimal strategy combination for integrated transport policy. Finally, the relationships between quantified objectives, policy combinations, and assessment performances would be analyzed using the proposed model in this study. The results can also provide a reference to decision makers when drafting urban integrated transport policies.