Identifying and prioritising effective parameters in urban bridge maintenance using fuzzy logic

Bridges are one of the key components of the transportation network infrastructure. Constructing bridges requires a large investment. To this end, identification of effective parameters in urban bridge maintenance plays an important role. Hence, the present study aims to prioritise these parameters in metropolitan Tehran, Iran. For this purpose, fuzzy decision making methods were used in the following phases: (i) data analysis to evaluate research indicators; (ii) evaluation of descriptive statistics parameters in factors analysis; (iii) monitoring and screening factors; and (iv) prioritising factors. The statistical population was estimated to be 200 people and Morgan’s table was used to determine the sample size; the minimum sample size was calculated to be 127 (S = 127) and questionnaires were given to 127 experts. The results provided six main factors: structural indicators (reliability = 0.84, validity = 0.64), climate and hydrology (reliability = 0.89, validity = 0.51), safety (reliability = 0.94, validity = 0.62), strategic (regional) importance (reliability = 0.62, validity = 0.94), budget (reliability = 0.88, validity = 0.66) and traffic and paving (reliability = 0.87, validity = 0.52). Based on the results, three factors with a higher rank related to each of the main indicators were prioritised. The results can be used to determine the status of the existing bridges in a transportation network based on the damage observed.