Simulation results for a daily activity chain optimization method

A growing trend, especially in urban environments, is observable towards flexibility in times and locations of activities performed during the day by passengers. In order to optimize the organization of daily activity chains a novel method was elaborated, which introduces flexible demand points. The main idea is that some activities are not necessarily fixed temporally and spatially, therefore they can be realized in different times or locations. Using flexible demand points the method finds all possible combinations and chooses the optimal set of activities by implementing TSP-TW algorithm. The optimum criterion was set as the minimum travel time. The algorithm takes into consideration many constraints, as opening times of the shops or maximum waiting times before the planned arrival. The application of the method results in shorter activity chains and a decrease of travel time for passengers, which has also economical and sociological benefits in long term.

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