<p>Increasing fuel consumption rates not only impose high costs on society, but also increases the environmental pollution, thus endangering the health of human society. This paper proposes an optimization method for automated determination of highway vertical alignment taking into account fuel consumption and road construction costs simultaneously. To solve the problem, a bi-level framework has been considered to adopt the ant colony optimization algorithm. In the upper-level problem, the optimal elevation of the central axis of road is determined with respect to the lowest possible total construction cost and fuel consumption cost, while satisfying mandatory safety and comfort criteria. The lower-level problem minimizes the construction cost through a linear mathematical programming model, instead of using the conventional geometric methods. Results show that: (a) during a conventional road life cycle, the fuel consumption costs are comparable with the cost of construction and, it cannot be ignored in the design phase; and b) the run-time of the proposed algorithm is satisfactory, so as it can be used in real projects in a reasonable time. The proposed algorithm is approximately 5 times faster than a complete enumeration method for projects with length of 500&#xa0;m. The proposed algorithm converges after about 40 iterations with the maximum number of objective function evaluation of 25 (number of ants) in each iteration. Also, it has been shown that ACO is a more efficient optimizer for the proposed bi-level approach than the two other metaheuristics frequently used in the literature, GA and PSO.</p>