Pavement Preservation Optimization Considering Multiple Objectives and Budget Variability

Abstract

Pavement preservation programming often involves multiple objective considerations. Traditional single-objective optimization frameworks consider one single objective while imposing competing objectives as constraints in the optimization formulation. This paper proposes an approach for pavement preservation programming that uses multiobjective optimization and chance constraints. This approach can handle multiple incommensurable and conflicting objectives while considering probabilistic constraints related to the available budget over the planning horizon. The implementation of the approach in a case study with two conflicting objectives of: (1) maximizing the network level of service in terms of weighted average state condition; and (2) minimizing the total preservation cost, shows that its application provides a practical and flexible tool to determine optimal allocation of resources for pavement preservation that reflects agency goals, resource limitations, and performance targets.