Capital-constrained maintenance scheduling for road networks considering traffic dynamics

Road network maintenance scheduling mainly considers budget limits in the previous studies and largely ignores the capital constraints. This study proposes a bi-objective mixed integer programming model, in which the net present value (NPV) is maximized and the increased total system travel time (ITSTT) due to maintenance activities under the capital constraints is minimized. Since the road network flows cannot reach an equilibrium state overnight due to the variation of network capacity, a link-based day-to-day dynamics model is developed to simulate the transient fluctuation in the traffic flows and calculate the total system travel time of each day. The bi-objective model is solved by the nondominated sorting genetic algorithm-II (NSGA-II) that generates a set of optimal Pareto solutions. The TOPSIS method is then adopted to determine the best compromise solution. Finally, a case study is conducted to demonstrate the effects of key parameters on the values of the two objectives.

Automated summary

This study proposes a bi-objective mixed integer programming model that considers the capital constraints in road network maintenance scheduling. A link-based day-to-day dynamics model is developed to simulate the transient fluctuation in traffic flows, and a nondominated sorting genetic algorithm-II (NSGA-II) is used to solve the bi-objective model and generate optimal Pareto solutions. The TOPSIS method is then adopted to determine the best compromise solution.