Dynamic traffic assignment (DTA) has been a topic of substantial research in the last two decades and it has recently received growing attention, with the news that it will utilise Advanced Traffic Information Systems (ATIS) applications. However DTA has many mathematical difficulties in searching its solution due to the complexity of spatial and temporal variables. Although many solution algorithms have been developed, conventional methods cannot find a solution when an objective function or constraints is not convex. In this paper, a new method using a genetic algorithm (GA) is provided to solve the DTA model. To apply this new method, the DTA model was formulated based on Merchant-Nemhauser's model (1978), which has a nonconvex constraint set. To handle the nonconvex constraint set, the GENOCOP III system, which is one of the GAs, is used in this study. Results for the sample network have been compared with the results of conventional method. For the covering abstract see ITRD E114174.
Abstract