A multi-objective optimization based on genetic algorithms for the sustainable design of Warm Mix Asphalt (WMA)

Abstract

ABSTRACT In this research, a methodology was developed to optimize the design of Warm Mix Asphalt (WMA) with the inclusion of three recycled materials as partial replacement of natural aggregates (NAs), namely Crumb Rubber (CR), Reclaimed Asphalt Pavement (RAP), and Recycled Concrete Aggregate (RCA). The methodological proposal is composed of 4 sections denominated: (I) environmental module, (II) economic module, (III) decision-support module, and (IV) results report module. Initially, a Life Cycle Assessment (LCA) is carried out to quantify the environmental impacts associated with WMA production. Similarly, in the second module, a Life Cycle Costing (LCC) is performed to estimate the financial investment required by the process under evaluation. Meanwhile, a computational model based on genetic algorithms (GAs) is created in the decision-support module to execute multi-objective optimization (minimization of costs and contaminating potential). In the last module, the more accurate WMA designs are presented employing a Pareto front, ternary plot, composition pie chart, and statistical analysis of the influence of the CR, RAP, and RCA on the validation criteria. This study concludes that even under long hauling distances and huge prices, it is possible to design WMA with CR, RAP, and/or RCA additions that form sustainability benefits compared to conventional WMA.