A practical method for the optimization of daily activity chains including electric vehicles

Abstract

The focus of this paper is to introduce a methodology for the optimization of daily activity chains of passengers, who use Electric Vehicles (EVs) in order to fully cover their transportation needs and attend activities in their daily life. An approach has been developed using a Genetic Algorithm (GA) framework to optimize the order, the locations of activities, the modes of transport and the travel time between the activities. The priorities of the passenger concerning flexibility were considered, as well as, special constraints that are related to the limited range of the EVs. The methodology consists of the modelling and the solution approach. While the first constitutes the basis of the approach and gives form to the solution space of the problem, the second includes the rules to be followed during the exploration of that solution space according to the GA framework. Our methodology allows to incorporate more parameters of the real-world problem and derive solutions for metropolitan size urban environments within reasonable computation times.