Nowadays, growing population and development of cities have resulted in increasing usage of cars in moderate and large cities, which has caused traffic congestion in the urban traortation network, which has been one of the most important concerns of authorities and people. Increased traffic jam has always led to more disorder in car movements, decreasing in citizens’ efficiencies, tiredness of community, and increasing in amount of air pollution and sound. One of the effective solutions is expending public traortation as well as increasing it’s accessibility, and reducing it’s costs. In addition, it should be noted to the importance of creating proper space for parking up cars. Reaching such conditions requires appropriate management and correct design of urban traortation, one of which is using proper park and ride in urban traortation networks. In this study, a mathematical programming has been presented to specify optimum site to locate park and ride facilities in the urban traortation network, and by regarding various stakeholders’ opinions, it is tried to consider the most important goals of such facilities like reducing traffic jam and pollution, decreasing in traortation costs, and minimizing spent time in the traortatin network along with maximizing exploiting park and ride facilities. Results indicate that the proposed model can be employed to distribute park and ride facilities equally in the urban traortation network to maximize covering of demands and reduce their travel time and costs. As the model is a type of Np-hard problems, a metahuristic approach has been adopted in this thesis to solve the model in moderate and large sizes. Solved problems indicate that the presented metaheuristic algorithm (ALNS-SA) is efficient and can solve large- sized problems with high quality answers in a little time. Finally, a case study is presented to locate park and ride facilities in the urban traortation network of Isfahan metropolitan. Keywords: Urban traortation network, Park and ride, Logit utility function, ALNS-SA algorithm
