  Purpose: This paper aims to propose an integration of the analytic hierarchy
process (AHP) and data envelopment analysis (DEA) methods in a multiattribute
grey relational analysis (GRA) methodology in which the attribute weights are
completely unknown and the attribute values take the form of fuzzy numbers.
  Design/methodology/approach: This research has been organized to proceed
along the following steps: computing the grey relational coefficients for
alternatives with respect to each attribute using a fuzzy GRA methodology. Grey
relational coefficients provide the required (output) data for additive DEA
models; computing the priority weights of attributes using the AHP method to
impose weight bounds on attribute weights in additive DEA models; computing
grey relational grades using a pair of additive DEA models to assess the
performance of each alternative from the optimistic and pessimistic
perspectives; and combining the optimistic and pessimistic grey relational
grades using a compromise grade to assess the overall performance of each
alternative.
  Findings: The proposed approach provides a more reasonable and encompassing
measure of performance, based on which the overall ranking position of
alternatives is obtained. An illustrated example of a nuclear waste dump site
selection is used to highlight the usefulness of the proposed approach.
  Originality/value: This research is a step forward to overcome the current
shortcomings in the weighting schemes of attributes in a fuzzy multiattribute
GRA methodology.
  Keywords: Data envelopment analysis, Grey relational analysis, Analytic
hierarchy process, Multiple attribute decision making, Fuzzy numbers,
Weighting.
