Tools to Support Pavement Management Investment Decisions for Achieving Multiple Target Objectives in a Local Agency

Multiple objectives are often used by agencies trying to manage pavement networks. If the goal is to achieve the target objectives at the minimum cost, tools are needed to assist agencies in identifying investment strategies capable of meeting target objectives while minimizing costs. A tool to identify the best combination of projects to meet target objectives at the minimum cost while maximizing treatment effectiveness is needed. Two alternative methods are compared for solving the allocation problem and for achieving the agency’s desired multiple objectives within pavement network condition constraints. The first method is the dynamic bubble-up technique (DBU) which is based on a sequential year ranking method. The second method is a multi-objective optimization model that uses integer programming techniques to estimate the investment needs required to meet the target objectives over a planning horizon. Both methods use concepts developed for the pavement management system supported by the Metropolitan Transportation Commission in the San Francisco Bay Area (MTC-PMS). Findings are presented from a case study conducted to assess how funding allocation methods influence maintenance and rehabilitation budget estimates over a planning horizon and consequently affect the future condition of the pavement network. Recommendations are also provided for incorporating the new methods into practical tools to improve existing pavement management practices.