The optimal Site selection operation is one of the most important challenges facing planners. Many location-allocation models have been developed based on multi-criteria decision making process. Recent methods take into account site, network, and user characteristics to determine the appropriate location. The development of optimum system has been a growing focus for most authorities across the world. It is generally thought that utlities allocation is the ultimate goal for service providers, which has been attributed to giving assistance in a time- and cost-efficient manner. In this paper, a multi-criteria decision making approach was implemented in two steps. Analytical hierarchy process (AHP) was adopted in the first step to determine the criteria weights. Results of AHP showed that response time had the highest weight among other criteria. Ranking of different alternatives was conducted in the second step using RAFSI model to choose the optimal location. Model ranking clearly indicated road-network as the best alternative to locate EMS centers.
Road maintenance is essential to the growth of the transportation infrastructure and, thereby, has a big impact on a nation's overall economic stability and prosperity. It is impossible to simultaneously monitor and maintain the entire network. As a result, transportation authorities are eager to develop scientific foundations for assessing the importance of maintenance tasks within the network of roads. Hence, pavement assessment methods are needed to establish the priorities and achieving the most convenient level of service. In this study, a road stretch was assessed using the sixteen criteria in the Distress Identification Manual for pavement defects, using pavement condition index (PCI) and multi-criteria decision-making models (MCDM). The two methods were compared to determine the possibility of using MCDM. The study came to the conclusion that MCDM is reliable in assessing pavement performance because both methods indicated that the road pavement is deteriorating.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.