Comparative analysis of test cases of the activity chain optimization method

Abstract

Abstract There is a growing interest in the literature regarding the flexibility of activities and reduction of travel times in an urban environment. For the optimization of daily activity chains a method has been elaborated, which includes the temporal and spatial flexibility of activities. In the course of the optimization process possible alternatives are searched using a modified version of the Traveling Salesman Problem with Time Window. The algorithm provides an optimal order of activities as the minimum of the pre-defined cost function. In our case the cost function is travel time. The optimization process results in travel time reduction of the users. In order to provide some insight regarding the performance of the optimization, application oriented simulations are realized on a real transportation network using real travel time information. Three transportation modes are considered: car, public transport and combined (public transport with car-sharing option). We conclude that with the use of the optimization algorithm approximately 20-25% travel time reduction can be achieved, but the exact value highly depends on the original location of the activities.