An integrated decision support system to achieve sustainable development in transportation routes with traffic flow.

Due to the growing population and demand, transportation planning has received special importance in the context of supply chain management. One of the major challenges in transportation planning is the traffic problem. This challenge affects the safety, environmental, and efficiency factors of transportation systems. Accordingly, in this study, the routes, which are important pillars of transportation planning, are examined from the perspective of sustainability. In this regard, a novel decision support system is developed, wherein at first, some decision-making methods including Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), entropy technique, Nash equilibrium point (NEP), and data envelopment analysis (DEA) are employed to analyze and determine unstable routes. Then, a bi-level leader-follower multi-objective optimization model is developed, based on the vehicle types, to evaluate the routes at different time intervals and identify the most efficient time intervals as a traffic pattern. Finally, the proposed models are implemented in a real case study based on the freeways in Tehran. According to the main finding, it is revealed that heavier and bulkier vehicles have a greater impact on road instability.