Selection of the best supplier with the help of random data envelopment analysis (case study: Khatam Al-Anbia construction site)
Subject Areas : Applied Mathematics ModelingAli Izadikhah 1 , Mehrzad Navabakhsh 2
1 - Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
Keywords: supplier, Khatam headquarters, Stochastic Data envelopment analysis, DEMATEL, network analysis process,
Abstract :
Data envelopment analysis is a non-parametric method for evaluating the efficiency of decision-making units, which recognizes the relative efficiency of decision-making units based on mathematical programming. Although data envelopment analysis has many advantages, one of the weaknesses in the data envelopment analysis model is that, in fact, data envelopment analysis does not allow random changes in input and output. However, in many. Finally, the results of determining the weight of criteria and sub-criteria with the help of ANP and the results of ranking the suppliers with the help of stochastic DEA have been compared and to select the supplier The final decision will be taken by the appropriate provider. Using the random data envelopment analysis technique, to evaluate and rank 20 supplier companies of Khatam al-Anbia construction site during the period of 1389-1400. In this research, we introduced data envelopment analysis with random data, random planning, efficiency Randomness and random ranking have been discussed. In this research, random data were determined by using mean and variance estimates for different inputs and outputs, and finally, random models and random super-efficiency were converted into deterministic models. Using the software, we have determined the efficiency and ranking of the decision-making units. The results showed that in five levels α = 0.1, α = 0.2, α = 0.3, α = 0.4, α = 0.5, Amitis company has the highest efficiency rating and Madesa company has the lowest efficiency rating.