SA-IP method for congestion pricing based on level of service in urban network under fuzzy conditions

This paper proposes a new hybrid method namely sa-ip including simulated annealing and interior point algorithms to find the optimal congestion prices based on level of service (los) in order to maximize the mobility in urban network. by considering six fuzzy los for flows, the congestion prices of links can be derived by a bi-level fuzzy programming problem. the objective function of the upper level problem is to minimize the difference between current los and desired los of links. in this level, to find optimal prices a simulated annealing algorithm is used. the lower level problem is a fuzzy flow estimator model with fuzzy link costs. applying a famous defuzzification function, a real-valued multi-commodity flow problem can be obtained. then a polynomial time interior point algorithm is proposed to find the optimal solution regarding to the estimated flows. in pricing process, by imposing cost on some links with los f or e, users incline to use other links with better los and less cost. during the iterations of sa algorithm, the los of a lot of links gradually closes to their desired values and so the algorithm decreases the number of links with los worse than desirable los. sioux falls network is considered to illustrate the performance of sa-ip method on congestion pricing based on different los. in this pilot, after congestion pricing, the number of links with los d, e and f are reduced and los of a great number of links becomes c. also the value of objective function improves 65.97% after toll pricing process. it is shown that the optimal congestion price for considerable network is 5 dollar and by imposing higher toll, the objective function will be worse.