We first propose the constrained shortest path problem with stochastic correlated link travel times.
A 0–1 integer programming model for the proposed constrained shortest path problem is formulated.
A specific Lagrangian relaxation-based approach is presented to relax the hard constraints.
An algorithmic framework is designed to minimize the gap between the upper and lower bounds.
The effectiveness of proposed approaches is verified by different scales of transportation networks.