Abstract—The goal of this research is offering an optimum model for the multi-modal public transportation fleet including LRT and the bus system of Tabriz city with the approach of reducing waiting time for the LRT passengers and scheduling the headway of the fleet. Attending the specifications of the public transportation system and the trip quality of the users of that part of urban transportation system from origin to destination, the trip times more significant than any other factors in the desirability of public transportation system and the amount of its use. As, by reducing the trip time of the passengers, public transportation system is selected as the cheapest and the most safe part of urban transportation system by the users. In this study a dynamic model is presented to determine the optimum assignment of the public transportation fleet in which the optimum policy and combination of the fleet is introduced by marking the joint stations between the lines of LRT and bus lines and also specifying the chosen bus lines for changing the fleet of them and then traffic analysis of urban transportation network according to each of the conversion policies of the fleet. The results get from the optimum model indicates that as for the interference of bus line and personal network, the increase of the bus lines fleet causes more crowding in some paths of the network (from origin to destination) and as such swing of the spent time and traversed distance in the network. This increases the costs for the users of the network. Therefore a assignment of the fleet is desired that makes the least cost for the users of the network.
Index Terms—Multi-modal public transportation, waiting time, optimum combination of the fleet.
Vahid Navadad is with the Marand Branch, Islamic Azad University, Maran, Iran (e-mail: v.navadad@ marandiau.ac.ir).
Cite: Vahid Navadad, "A Dynamic Supply-Demand Model of Fleet Assignment with Reducing Waiting Time of the Passengers Approach (LRT and Bus System of Tabriz City)," International Journal of Modeling and Optimization vol. 2, no. 2, pp. 162-167, 2012.