Multi-objective optimization of flexible pavement design from an environmental and economic perspective

In recent years, construction companies have been pressured by clients to deliver infrastructure that are not only affordable, but also more environmentally friendly. Flexible road pavements are an example. These are multi-layered systems where each layer has its own type of mixture and thickness. The number of asphalt mixtures available to contractors is increasing in size, creating a wide range of flexible pavement design alternatives. These increases make it difficult for the pavement designer to find simultaneously the most affordable and environmentally friendly design, while also ensuring that pavement performance requirements are met. This paper employs a multi-objective optimization (MOO) approach that uses the weighted sum method and genetic algorithm (GA) to find optimal pavement designs by minimizing the Environmental Costs Indicator (ECI) alongside construction costs. The MOO approach was applied to five different pavement design settings, including a real-life case study, to find optimal solutions for each setting. This approach enables the reduction of both ECI and construction costs of pavement designs comparatively with those made by the pavement designer. We recommend that the design responsibility of flexible pavements be handed over from client to contractor to prevent the design of pavement structures that result in unnecessary environmental impacts and costs.