Abstract: Given the abundance of condition data regularly collected for major roadways, machine learning has the potential to enhance pavement deterioration modeling. This is particularly important for recycling-based rehabilitation ...

Abstract: Recent data trends and analysis have highlighted the need to incorporate more imprecise, ambiguous, and unreliable data into uncertainty analysis traditionally handled by probability theory. However, data fraught with ...

Abstract: The economic crisis that currently affects some Western countries has reduced the employability of graduates in the construction industry. Nevertheless, many young professionals consider this situation as an opportunity ...

Abstract: United States highway agencies use best-value procurement with a fixed price to select design builders. This method enables public agencies to choose the best proposer by assessing several factors in addition to price. ...

Abstract: Traditional design–bid–build guidelines suggest that engineering estimates should be within +/−10% of the lowest contractor bid and recommend this value as a reference to identify anomalies in the bidding process. This ...

Abstract: Green Public Procurement (GPP) is an alternative for public agencies to purchase goods and services with a reduced environmental impact. GPP encourages the integration of environmental criteria in the procurement procedure ...

Abstract: In best-value procurement, current practice shows that cost is frequently more influential than noncost factors, and consequently, the lowest bidder is chosen in most cases; thus, a best-value selection is not achieved. ...

Abstract: This paper presents findings of a recent study that was conducted in Canada on the quantification of pavement sustainability. The ultimate goal of this study was to develop a framework and explore the use of multicriteria ...