Multi-objective optimization for sustainable road network maintenance under traffic equilibrium: Incorporating costs and environmental impacts

It is vital to consider traffic dynamics and environmental burdens when developing sustainable long-term maintenance schedules for asphalt road networks. This paper presents a multi-objective optimization model incorporating the interactions between pavement condition and traffic dynamics to identify a wide range of optimal solutions for the planning of multi-year road network maintenance. The multi-objective optimization model integrates three elements: agency costs, user costs and greenhouse gas (GHG) emissions. The modified non-dominated sorting genetic algorithm II (NSGA II) with a mixed initial population is proposed to search for the well-distributed Pareto frontier, to assist decision-makers to conduct trade-off analysis. A hypothetical road network maintenance case study was conducted to test the method. Compared with conventional NSGA II, the proposed method identifies more candidate solutions for the three-objective optimization problem. Trade-off analysis was carried out among the three objectives in both two and three dimensions. The results show that the proposed method generates effective maintenance schedules that minimize user costs and GHG emissions in an equilibrated network. In addition, the minimum total emissions resulting from maintenance and vehicles depend on the sensitivity of pavement deterioration to traffic loading.