جستجوی مقالات مرتبط با کلیدواژه « Preference selection index » در نشریات گروه « علوم انسانی »

Due to the unfair distribution of facilities and services, the issue of inequalities in various fields, especially in the education sector, is one of the issues that requires expert studies. In the present research, the analysis of educational indicators in Iran has been done. The research approach is quantitative and the final study of 18 research variables has been done using multi-indicator decision-making techniques such as Vikor technique and preference selection index. The results of Vikor technique show that Tehran has the highest score with a score of (0/0000). Khorasan Razavi is in a good position after Tehran with a score of (0/1830). In VIKOR technique, Ilam province with a score of (0/9759) and South Khorasan province with a score of (0/9763) have the lowest scores, and the status of educational indicators in them is evaluated as poor and they need serious attention. The results of the preference selection index show that Tehran with a total score of (0/9509) and Razavi Khorasan with a total score of (0/8605) have obtained the highest scores in the preference selection index. The scores obtained from the preference selection index show that Semnan province with a total score of (0/2493), Qom province with a total score of (0/2693), Ilam province with a total score of (0/2730), and South Khorasan province with a total score of (0/2842) have the lowest scores. By using the Average nearest neighborhood the pattern of distribution of educational services in Iran, 1/530966, Z score 5/655593, and PValue 0/000 have been obtained. Based on the Average nearest neighborhood, the pattern of distribution of educational services in Iran has been scattered. Based on Moran's coefficient, the pattern of distribution of educational variables in Iran is Random.

Housing is one of the basic and important dimensions of quality of life to achieve development, it is urban and regional stable and plays a vital role in the Economic development of Society. Since the need for housing is one of the most basic human needs, this research it was done with the aim of ranking the status of construction and housing industry in Iran.

In this retrospective study, the data of the construction and housing industry in 2018 was collected in 31 provinces of Iran through statistical yearbooks. Analysis the indicators of this industry using the preference selection index which is one of the latest multi-criteria decision-making techniques were carried out.

Tehran and Isfahan provinces were placed in the very preferred group with Preference selection index of 0.7076 and 0.5747 respectively, and the condition of building and housing indicators in these provinces was evaluated as good. The provinces of Bushehr, Golestan, Semnan, Ilam, Kohgiluyeh and Boyar Ahmad were in the low preference group with Preference selection index of 0.0632, 0.0624, 0.0537, 0.0303 and 0.0276 respectively, and the condition of building and their housing was bad.

Preference selection index is a suitable method for ranking the situation Building and housing in Iran. The provinces of Tehran and Isfahan are best and Ilam and Kohgiluyeh and Boyer Ahmad have the worst condition of buildings and housing.

Existence of urban green space is one of the prerequisites for achieving sustainable urban development and plays a key role in improving the quality of life of urban dwellers. The research is practical and quantitative in terms of purpose and nature and is of analytical-comparative type and using Preference selection index and multi-moora technique has been analyzed green space indicators in Isfahan metropolis. The research data is adapted from the statistics of Isfahan metropolis in 2019. The results of the preference selection index for the analysis of green space indicators in the metropolis of Isfahan show that the highest score belonged to regions 4, 6, 10 and 8. The lowest scores of the preference selection index were assigned to regions 2, 11 and 15. The results of applying the three approaches of multi-moora technique for the analysis of urban green space indicators show imbalance and inequality in 15 Regions of Isfahan metropolis. The highest score of the Ratio system approach was compared to region 10 and the lowest score of the Ratio system approach was assigned to region 11. The highest score of the Reference point approach belonged to region 14 and regions 11 and 3 obtained the lowest score of the Reference point approach. In the Complete multiplication approach, region 8 of Isfahan metropolis has the highest score and regions 11, 1, 2 and 14 have the lowest score. The difference between the scores obtained in the preference selection index and the three approaches of Multi Moora technique indicates the existence of inequality in the field of urban green space indicators in the fifteen Regions of Isfahan metropolis.

Increasing the complexity of decision-making problems leads to utilize a group of experts instead of one expert for evaluating the contractor selection problem. This paper proposes a hesitant fuzzy preference selection index method based on risk preferences of experts. The hesitant fuzzy set is used to cope with the uncertainty in vague/hesitant situations. Also, the compromise solution is proposed to compute the weight of each expert. Moreover, the proposed approach considers the quantitative and qualitative criteria and also assists the experts to reduce margin of errors by assigning some membership degrees for each contractor versus each criterion under a set. In addition, the expert's judgments are aggregated in the last step of proposed approach in the group decision process to avoid the data loss. In the presented approach, selecting the best contractor is based on closest to positive ideal and farthest from negative ideal, simultaneously. Finally, the proposed method is applied to a case in construction industry for selecting the suitable contractor, in which the obtained results are compared with two decision methods from the recent literature to indicate the efficiency and validity of the proposed method.