Restriction of the movement of heavy-trucks in a transportation network is a commonly used strategy to mitigate traffic congestion and pollution issues, especially in congested urban areas. However, the cost and capacity functions used in the literature are inadequate to describe the traffic dynamics in heterogeneous conditions. This paper proposes a systematic framework with new cost and capacity functions, to identify critical links in a network and to determine the minimum cost truck routes in the network by restricting trucks on identified critical links. A hierarchical mathematical programming framework with integer programming formulations are presented. The capacity and cost functions are derived based on a multiclass model and shockwave analysis to represent realistic traffic flow interactions between the trucks and cars. The model results are validated using VISSIM simulation, which shows that the total delay reduced and the network capacity utilization improved with truck restriction. © 2019 IEEE.