DEA-ANP sequential hybrid algorithm for multiple-criteria decision-making process, a long with an application

Nowadays that technology is improving at a fast rate with the acceptance of efficiency measurement methods, organizations can be adapted more quickly and take necessary precautions. Lots of models and techniques liable to efficiency measurements have been improved. Nevertheless, the important point to be considered is to know how to take advantage of these models. The application of an objective efficiency measurement is possible with the use of generally accepted scientific methods in process. In this study, the process of efficiency measurement is tackled with using multiple criteria decision-making processes where a sequential hybrid algorithm is proposed. Suggested algorithm in this literature has demonstrated considerable advantage over the already-existing methods. For complex decision making problems, an Analytic Network Process (ANP) and a Data Envelopment Analysis (DEA) have been used. The proposed algorithm has been designed for sequencing the multi input and output units. In the initial step of algorithm, all inputs and outputs of the units are formulated using DEA. These models are, then, decomposed in the LINDO package program; later in the second step, pair-wise comparison values with the help of ANP, are sequenced using the affection of binary correlation matrix. The DEA-ANP sequential hybrid algorithm may not be used instead of the DEA classification model. However, all units have been fully ranked, whether they have been efficient or inefficient beyond characterizing. This algorithm has been discussed in terms of its application in an example.