Itinerary Planning for Personal Intercity Trip in Transportation Networks by Genetic Algorithm

In this study, planning of activity-based personal trips in the public transportation networks that is of importance for tourist is developed. Public transportation networks are organized by time-dependent models. In this model the edge-weight is not constant and time-dependency of departure. Since trip planning has combinational nature and is optimization, therefor it is modeled with genetic algorithm. This algorithm is among the ways which use meta-heuristic search in order to find optimum solution. In this study structure is proposed that receives the raw data of day and time of the trip, the favorite cities of the traveler with their priority rating, the duration of activity in a particular city and its timing along with selected transportation networks from the traveler and designs trip planning in a way that in the allocated time the traveler gets the highest benefit rate of their visit and activity in the chosen cities. Among the purposes of this study are: modeling of personal activities, tip planning with the aims of optimize the time of trip and evaluating the proposed structure. In order to evaluate the proposed framework a series of data from timetables of transportation network of 15 Iran province centers for three transport networks: airplane, bus and train for travelling in the selected cities were collected and frameworks along with modeling were evaluated. So for its evaluation 50 trips with different starting time and tour duration were performed that in average have relative error 5.2%.