Optimization of Human Resources and Industrial Banks with Ambiguous Inputs Using Intelligent Fuzzy Mathematical Programming Approach

Abstract

<span style="font-size:11.0pt;font-family: " times="" new="" roman","serif";mso-fareast-font-family:"times="" roman";mso-bidi-font-family:="" mangal;mso-ansi-language:en-gb;mso-fareast-language:en-us;mso-bidi-language:="" hi"="" lang="EN-GB">This paper <span style="font-size:11.0pt;font-family: " times="" new="" roman","serif";mso-fareast-font-family:"times="" roman";mso-bidi-font-family:="" mangal;mso-ansi-language:en-gb;mso-fareast-language:en-us;mso-bidi-language:="" fa"="" lang="EN-GB">presents an integrated fuzzy data envelopment analysis (FDEA) and analytical hierarchy process (AHP) approach for optimization and ranking of industrial banks with ambiguous human resources indicators. FDEA is proposed to consider the uncertainty existed within qualitative indicators since in actual cases the criteria for evaluating human resources cannot precisely be measured. Also, AHP is used for identifying weights and priorities of different human resources indicators. Results were validated and verified by conventional mathematical models. The proposed approach can also be used for optimum human resources operation in large industrial banks. This is the first study that presents an integrated FDEA-AHP approach for ranking and optimization industrial banks with ambiguous human resources indicators.</span></span>