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A methodology for augmenting sparse pairwise comparison matrices in AHP: applications to energy systems

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Abstract

Multiple-attribute decision making (MADM) techniques can be used to provide a systematic approach to selection problems in energy engineering and management. They may be used for selecting the best technologies or policies based on environmental, technical, and socio-economic criteria. Among the many available MADM techniques, the analytic hierarchy process (AHP) has become one of the most widely used due to its effective hierarchical decomposition of complex problems. However, AHP may be tedious due to the large number of pairwise comparisons needed in large problems. Furthermore, in many cases, relevant information may also be available for determining criteria weights based on past decisions that have proven satisfactory in retrospect. Thus, we propose a simple methodology for augmenting sparse pairwise comparisons in AHP through a non-linear programming model that extracts a set of consistent weights from a priori ranking of a subset of alternatives. Two case studies on the ranking of bioethanol feedstocks and of CO2 storage sites are then shown to illustrate this technique.

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Abbreviations

I :

Set of all alternatives

I′ :

Set of alternatives for which a priori ranks are known

J :

Set of all criteria

J′ :

Set of criteria for which pairwise comparisons are known

J″ :

Set of criteria used in a priori ranks of original alternatives

\(a_{jj^{\prime}}\) :

Pairwise comparison ratio of criteria j and j′

A :

Pairwise comparison matrix

N :

Total number of criteria

x ij :

Score of alternative i with respect to criterion j

w j :

Weight of criterion j

y i :

Overall score of alternative i based on original set of criteria

z i :

Overall score of alternative i based on all criteria

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Acknowledgments

The authors are grateful for partial financial support of the Commission on Higher Education (CHED) through the Philippine Higher Education Research Network (PHERNet) Program on Sustainability Studies. We also wish to thank Dr. Kathleen B. Aviso and Dr. Nathaniel P. Dugos who provided inputs as domain experts in our case studies.

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Authors and Affiliations

  1. Chemical Engineering Department, De La Salle University, Manila, Philippines

    Raymond R. Tan & Michael Angelo B. Promentilla

  2. Center for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 1004, Manila, Philippines

    Raymond R. Tan & Michael Angelo B. Promentilla

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  1. Raymond R. Tan
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  2. Michael Angelo B. Promentilla
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Correspondence to Raymond R. Tan.

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Tan, R.R., Promentilla, M.A.B. A methodology for augmenting sparse pairwise comparison matrices in AHP: applications to energy systems. Clean Techn Environ Policy 15, 713–719 (2013). https://doi.org/10.1007/s10098-012-0555-5

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  • DOI: https://doi.org/10.1007/s10098-012-0555-5

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