Pavement Investment Programming for Secondary Roads Using Multiobjective Optimization and Chance Constraints

Pavement management includes three sequential levels: programming, project selection, and project level. At the programming level, decisions regarding the budgets and general resource allocations are made over an entire network. These decisions have great impact on the effectiveness of the other levels because they determine the allocation of resources. Current practices on management of secondary road pavements are often subjective because scarce resources concentrate on the primary systems. This paper proposes a practical decision-support model for pavement maintenance and rehabilitation (M&R) programming that uses multiobjective optimization and chance constraints. The model can handle multiple incommensurable and even partially conflicting objectives while considering probabilistic constraints related to the available budget over the planning horizon. The objectives considered include: (1) maximizing the network maintenance effectiveness in terms of weighted pavement effective life, (2) minimizing the percentage of pavement network in the lowest state, and (3) minimizing the total weighted maintenance cost. The implementation of the model in a simple case study with three partially conflicting objectives showed that its application is practical for supporting the management of secondary roads. It provides a flexible tool to determine optimal allocation of resources for pavement M&R that reflects agency goals, resource limitations, and performance targets.