Optimizing the rehabilitation efforts of aging transportation networks

Major roads and bridges in the United States are aging and deteriorating, which is causing significant human and economic losses. The required investments to rehabilitate these transportation networks exceed available funds and budgets. The rehabilitation efforts of these aging networks, therefore, need to be optimized to maximize their net benefits and reduce the effect of construction works on the traveling public. This paper presents the development of an innovative model aimed at aiding decision makers in planning and optimizing highway rehabilitation programs. This model provides new and unique capabilities, which include: allocating limited financial resources to competing highway rehabilitation projects, measuring the effect of rehabilitation efforts on network performance and road user savings, analyzing the expected benefits and costs of rehabilitation programs, and generating optimal tradeoffs between maximizing rehabilitation benefits and minimizing network service disruption using a genetic algorithm (GA)-based optimization module. An application example is analyzed to evaluate the performance of the proposed model and demonstrate its capabilities in identifying a wide range of optimal rehabilitation programs, in which each provides a unique and nondominated tradeoff between maximizing rehabilitation benefits and minimizing service disruption. This allows decision makers in departments of transportation to select and implement the rehabilitation programs that address their specific societal needs.