Hybrid Multiobjective Optimization Model for Regional Pavement-Preservation Resource Allocation

Because of a lack of reliable performance prediction models, many state departments of transportation (DOTs) use a needs-based budgeting process, namely, annual budget requests. Allocations of funding across maintenance activities and districts are developed on the basis of pavement maintenance needs derived from pavement inventory and annual or biannual condition data. This allocation of funding across maintenance activities and districts is challenging and often involves negotiation and balancing. A decision support model is proposed for the optimization of short-term pavement preservation budgeting based on two proven operations research techniques: goal programming for handling multiple objectives and an analytic hierarchy process for priority setting under multiple criteria. The model simultaneously considers two incommensurable and conflicting objectives: maximization of the preservation effectiveness in terms of extended service life and minimization of the total preservation cost. Application of the model is demonstrated with a short-term pavement preservation budgeting problem for a decentralized state DOT with nine maintenance districts. The illustrative example reveals that the proposed model is practical for supporting needs-based budgeting.