Case study for the selection of optimal asphalt wearing course types for heavily trafficked roads

TEN TAnother scientific article prepared by Hungarian partner KTI linked to the decision supporting model focusses on the sensitivity analysis of the model and presents a relevant case study.

The sensitivity analysis performed was concentrated on the modification of Ri factor as a result of changing criterion weights and variant evaluations. TOPSIS method was selected for the assessment of climate change effects on asphalt wearing course performance in four European regions.

The case study work started with the weighing of criteria. A decision making tree was compiled with requirements and criteria and indicators. For the evaluation of qualitative variables, verbal terms and triangular fuzzy numbers were identified. In the next phase, the weights of hierarchical structural elements were determined. The technical (functional) requirements were also shown and considered as the most important for the experts.

Then, five different variants (AC, BBTM, HRA, PA, SMA) were evaluated. For quantitative indicators, the value-ranges were identified with minimal, maximal and mean values. For qualitative indicators, the variants described by triangular fuzzy numbers were transformed to canonical forms using the graded mean integration method. By the help of TOPSIS method, the relative distances of variants from the ideal solution were calculated.  

The final ranking was as follows:

  1. SMA (stone mastic asphalt)
  2. HRA (hot rolled asphalt)
  3. BBTM (béton  bitumineux trés mince)
  4. AC (asphalt concrete)
  5. PA (porous asphalt).

As last step, a sensitivity analysis was completed proving again the preponderance of SMA.

The article can be downloaded by clicking the following link: