Simulation Results for a Daily Activity Chain Optimization Method based on Ant Colony Algorithm with Time Windows

In this paper, a new approach is presented based on ant colony algorithm with time windows in order to optimize daily activity chains with flexible mobility solutions. This flexibility is realized by temporal and spatial change of activities achieved by travellers during one day. With the injection of flexibility concept of time and locations, the requirements for such a transport system are high. However, our method has shown promising results by decreasing 10 to 20% the total travel time of travellers based on combining and comparing different transport modes including the private transport as well as the public transport and by choosing the optimal set of activities using our method.