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Growing Science » Decision Science Letters » Evaluation and selection of energy technologies using an integrated graph theory and analytic hierarchy process methods

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Decision Science Letters

ISSN 1929-5812 (Online) - ISSN 1929-5804 (Print)
Quarterly Publication
Volume 5 Issue 2 pp. 237-348 , 2016

Evaluation and selection of energy technologies using an integrated graph theory and analytic hierarchy process methods Pages 237-348 Right click to download the paper Download PDF

Authors: P. B. Lanjewar, R. V. Rao, A. V. Kale, J. Taler, P. Ocłoń

DOI: 10.5267/j.dsl.2015.10.001

Keywords: Analytic hierarchy process, Energy technology, Graph theory, Multiple attribute decision making, Preference index

Abstract: The evaluation and selection of energy technologies involve a large number of attributes whose selection and weighting is decided in accordance with the social, environmental, technical and economic framework. In the present work an integrated multiple attribute decision making methodology is developed by combining graph theory and analytic hierarchy process methods to deal with the evaluation and selection of energy technologies. The energy technology selection attributes digraph enables a quick visual appraisal of the energy technology selection attributes and their interrelationships. The preference index provides a total objective score for comparison of energy technologies alternatives. Application of matrix permanent offers a better appreciation of the considered attributes and helps to analyze the different alternatives from combinatorial viewpoint. The AHP is used to assign relative weights to the attributes. Four examples of evaluation and selection of energy technologies are considered in order to demonstrate and validate the proposed method.

How to cite this paper
Lanjewar, P., Rao, R., Kale, A., Taler, J & Ocłoń, P. (2016). Evaluation and selection of energy technologies using an integrated graph theory and analytic hierarchy process methods.Decision Science Letters , 5(2), 237-348.

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Journal: Decision Science Letters | Year: 2016 | Volume: 5 | Issue: 2 | Views: 2917 | Reviews: 0

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