Integer Programming of Maintenance and Rehabilitation Treatments for Pavement Networks

Abstract

A new approach to multiyear maintenance and rehabilitation (M&R) optimization programming for pavement network management is discussed; the approach can be used to help highway agencies make strategic decisions in choosing the optimal investment for their pavement networks. The M&R treatments are standardized in terms of costs, benefits, and performance impacts on the existing pavements. Each standardized pavement treatment strategy, ranging from minor and routine maintenance to major rehabilitation or reconstruction, is defined by its effect and improvement on the existing pavement serviceability. The optimization model is a cost-effectiveness-based integer M&R programming on a year-by-year basis. The objective of the optimization system is to select the most effective M&R projects for each programming year. The optimization system can also be used to calculate the minimum budget requirements for maintaining a prescribed level of the pavement network performance or serviceability. In such a case, sensitivity analysis can be performed to evaluate the annual budget effect on individual pavement performance. The prediction of individual pavement deterioration is modeled as a time-related (nonhomogeneous) Markov transition process. The investigation described was primarily concerned with integration of the performance prediction model, the standardized M&R treatments, and the network optimization process. The principle and methodology developed can be applied to different levels of pavement network management. Finally, a sample application of the integrated pavement optimization model is demonstrated.

Benefit maximisation based on aggregated condition indices: drawbacks for selection of pavement treatments

“…The IBC formulation can be solved exactly using binary integer mathematical programming (BIP). Integer formulations of the M&R optimisation problem are common in pavement management (Haas et al 1994, Li et al 1998, Ferreira et al 2002, Wang et al 2003, Scheinberg and Anastasopoulos 2010. A multi-year binary integer programme, minimising life cycle costs or maximising benefits is presented in Figure 3 (a).…”

A Two‐Stage Stochastic Model for Maintenance and Rehabilitation Planning of Pavements

“…Equations (28) and (29) are the constraints to avoid the application of more than one M&R action from a M&R policy 8 Mathematical Problems in Engineering…”

“…Durango-Cohen took pavement deterioration models as nondeterministic models and evaluated the M&R policies efficiently when imprecise pavement deterioration models are available [27]. Some researchers found the uncertainty in pavement deterioration models as function of uncertainty in pavement structural design, traffic and climatic conditions, and pavement age [28][29][30][31][32]. However, it is important not to restrict the uncertainty to the pavement deterioration [23].…”

Toward Sustainable Pavement Management

“…Mathematical formulations for optimizing decisions in a network of spatially distributed assets can be found in Watanatada et al (2), Li et al (29), and Vitale et al (30). A typical application of the optimization process seeks to maximize the aggregated network level of service (Equation 1) subject to a given budget per planning period (B t ).…”