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Introducing a nonlinear programming model and using genetic algorithm to rank the alternatives in analytic hierarchy process

عنوان مقاله: Introducing a nonlinear programming model and using genetic algorithm to rank the alternatives in analytic hierarchy process
شناسه ملی مقاله: JR_APRIE-1-1_002
منتشر شده در در سال 1393
مشخصات نویسندگان مقاله:

Sahar Khoshfetrat - Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Farhad Hosseinzadeh Lotfi - Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran.

خلاصه مقاله:
As ranking is one of the most important issues in data envelopment analysis (DEA), many researchers have comprehensive studies on the subject and presented different approaches. In some papers, DEA and Analytic hierarchy process (AHP) are integrated to rank the alternatives. AHP utilizes pairwise comparisons between criteria and units, assessed subjectively by the decision maker, to rank the units. In this paper, a nonlinear programming (NLP) model is introduced to derive the true weights for pairwise comparison matrices in AHP. Genetic algorithm (GA) is used in order to solve this model. We use MATLAB software to solve proposed model for ranking the alternatives in AHP. A numerical example is applied to illustrate the proposed model.

کلمات کلیدی:
Data envelopment analysis (DEA), Analytic Hierarchy Process (AHP), Genetic algorithm (GA)

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1360144/