ABSTRACT
ABSTRACT Multi-objective optimization (MOO) methods have drawn an increasing interest from transportation agencies as a tool to help to enhance pavement sustainability. Among other merits, it allows identifying solutions in which the often conflicting economic, environmental and technical performances are simultaneously optimized. Current approaches for incorporating sustainability concerns in the optimization-based decision-making process in pavement management consist of minimizing either the greenhouse gases (GHG) emissions or the energy consumption while ignoring other impact categories. However, the design of sustainable solutions requires a more comprehensive analysis that consider a wider set of impacts related to the natural environment, human health and non-renewable resources, as well as economic indicators.
To address this multidimensional problem, this study presents the development and application of a many-objective optimization (MaOO) framework that combines a comprehensive and integrated pavement life cycle costs (LCC) – life cycle assessment (LCA) model that covers the whole pavement's life cycle, a multi-objective evolutionary algorithm (MOEA) and a multi-dimensionality reduction method. This method allows for overcoming both the model solving difficulties arising from considering simultaneously a large number of objective functions and the limitations associated with the use of aggregated metrics that translate several environmental metrics into a single indicator, without disturbing the main features of the problem. The potentialities of the proposed framework are illustrated through a French case study consisting of identifying sustainable pavement maintenance and rehabilitation (M&R) strategies for a road pavement section that concurrently minimize the net present value of the life cycle costs incurred by the highway agency and multiple life cycle environmental indicators.
