A NOVEL APPROACH TO SUPPORT MAJORITY VOTING IN SPATIAL GROUP MCDM USING DENSITY INDUCED OWA OPERATOR FOR SEISMIC VULNERABILITY ASSESSMENT
- 1Dept. of Surveying and Geomatics Eng., University of Tehran, Tehran, Iran
- 2Center of Excellence in Geomatics Eng. in Disaster Management, Dept. of Surveying and Geomatics Eng., College of Eng., University of Tehran, Tehran, Iran
- 3Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Eng., University of Tehran, Tehran, Iran
Keywords: Group MCDM, Majority Voting, Density Induced OWA, Earthquake, Vulnerability Assessment, Tehran
Abstract. Being one of the most frightening disasters, earthquakes frequently cause huge damages to buildings, facilities and human beings. Although the prediction of characteristics of an earthquake seems to be impossible, its loss and damage is predictable in advance. Seismic loss estimation models tend to evaluate the extent to which the urban areas are vulnerable to earthquakes. Many factors contribute to the vulnerability of urban areas against earthquakes including age and height of buildings, the quality of the materials, the density of population and the location of flammable facilities. Therefore, seismic vulnerability assessment is a multi-criteria problem. A number of multi criteria decision making models have been proposed based on a single expert. The main objective of this paper is to propose a model which facilitates group multi criteria decision making based on the concept of majority voting. The main idea of majority voting is providing a computational tool to measure the degree to which different experts support each other’s opinions and make a decision regarding this measure. The applicability of this model is examined in Tehran metropolitan area which is located in a seismically active region. The results indicate that neglecting the experts which get lower degrees of support from others enables the decision makers to avoid the extreme strategies. Moreover, a computational method is proposed to calculate the degree of optimism in the experts’ opinions.