Path planning with the aim of finding an optimal path on a multi-modal transportation network, including public transport services and private services, is essential to assist people for using transport network infrastructures. Transportation networks are classified into two categories of time-independent and time-dependent models. The main difference between the two models is constant edge-weight in the first model and time-dependency of departures in the second. The goals of this study is modeling transport networks with different periods, proposing a new method for data storage and developing the Dijkstra’s algorithm for planning on multi-modal suburban transportation networks according to time and personal interests, implementing the proposed process on a dataset and evaluating the results. In this study, a framework is proposed that receives departure time, the source and destination cities as well as user’s priorities of transportation networks and proposes a path planning.