This research develops a non-linear continuous optimisation model to estimate tolls for multi-class and multi-period traffic considering integral social costs such as congestion externalities, pavement damage, environmental emissions, operational travel costs, and user travel time cost, in addition to maintenance and construction of road infrastructure costs. The approach uses social welfare principles, formulating a function to calculate the social welfare of a multi-class flow that moves in multiple periods based on a stochastic discrete choice model and considering infrastructure financing constraints. A case study was conducted applying the model to a road in the Colombian Caribbean region and estimated the value of tolls using the particle swarm optimisation heuristic. Results showed that infrastructure policies considering partial financing resulted in higher social welfare values. Scenarios requiring toll revenue to be higher than infrastructure cost can shrink demand and cause distributive issues.