A review of application of multi-criteria decision making methods in construction

Construction is an area of study wherein making decisions adequately can mean the difference between success and failure. Moreover, most of the activities belonging to this sector involve taking into account a large number of conflicting aspects, which hinders their management as a whole. Multi-criteria decision making analysis arose to model complex problems like these. This paper reviews the application of 22 different methods belonging to this discipline in various areas of the construction industry clustered in 11 categories. The most significant methods are briefly discussed, pointing out their principal strengths and limitations. Furthermore, the data gathered while performing the paper are statistically analysed to identify different trends concerning the use of these techniques. The review shows their usefulness in characterizing very different decision making environments, highlighting the reliability acquired by the most pragmatic and widespread methods and the emergent tendency to use some of them in combination

A spatio-temporal cluster analysis of structurally deficient bridges in the contiguous USA

The disease surveillance software SaTScan™ is used to identify spatial and space-time clusters of counties with unusually high counts or rates of SD bridges. Initially, a descriptive data analysis of over 600,000 bridges, on which data were available for 2017, identified the kind of material and design of all bridges. This was followed by analyzing data on SD bridges for the 3108 counties. The clusters were tested for significance with Monte Carlo study to designate significant SD clusters. While the purely spatial analysis was based on data for 2017, the spacetime analysis used data for the years 2006–2017. A Negative Binomial regression model was used in addition to a cluster analysis. Regression analysis was performed to adjust SD counts for several covariates or risk factors. This study identified counties with high rates of SD bridges as rural counties with old bridges where there is cold weather and low daily traffic.Journal ArticleFinal article publishe

A multi-criteria decision-making analysis for the selection of fibres aimed at reinforcing asphalt concrete mixtures

In the last few years, fibers have been proposed as one of the most important additives for the development of reinforced asphalt mixtures. The optimal fiber selection is a very complex task, as an extensive range of criteria and alternatives have to be taken into account. Decision support systems have been applied in the construction sector, but not for selecting fibers for bituminous mixtures. To fill this gap, two Multi-Criteria Decision-Making Analysis methodologies for the selection of the best fiber to be used in Asphalt Concretes are presented in this paper. The Weighted Aggregate Sum Product Assessment (WASPAS) methodology and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) integrated with Fuzzy Analytic Hierarchy Process (FAHP) are used to evaluate the effect of various types of fibers on the mechanical performance of bituminous mixtures. Given the uncertainty involved, a stochastic simulation is proposed using the Monte Carlo method. A statistical analysis is carried out to verify the results obtained. Both methods of multi-criteria analysis were effective, with TOPSIS being slightly more conservative in the assignment of performance scores. Synthetic fibers proved to be a suitable option as did fibers with high tensile strength and elastic modulus