Abstract Trucks generate more externalities (environmental and social) than passenger vehicles, especially when trucks divert off freeways. When toll charges increase, such as the significant recent rise in Mel-bourne, Australia, more trucks tend to avoid toll roads (quality roads), generating more externalities. This diversion adds sub-stantial negative impacts on residents, the environment, and so-ciety. In fact, determining an optimum toll charge for freight ve-hicles is a crucial decision to be made by policymakers consid-ering socioeconomic aspects. The objective of this study is to develop an approach to design an optimal toll pricing scheme for multiclass vehicles, including specific truck types, consider-ing both direct costs and externalities. Additionally, the study developed an approach to identify the tradeoffs between vari-ous objectives of the designed scheme considering given con-straints. Nonlinear programming and user equilibrium techniques are used to model the problem, and the costs (direct costs and externalities) are quantified for Victoria, Australia. This nonde-terministic polynomial-time hard (NP-hard), nonconvex problem with nonlinear constraints was solved using the nondominated sorting genetic algorithm (NSGA) II. The model was applied to both a small-sized hypothetical network and a real network, with static demand conditions to illustrate differences between common toll schemes. Results are presented for Pareto-optimal solutions.