Aggregation in the analytic hierarchy process: Why weighted geometric mean should be used instead of weighted arithmetic mean

作者：

Highlights：

• The results of aggregation by weighted arithmetic mean are normalization-dependent.

• Weighted arithmetic mean aggregation fails to reflect preference information well.

• Serious problems caused by the arithmetic mean aggregation shown on examples.

• Theorems claiming the superiority of geometric mean aggregation in AHP presented.

• Weighted geometric mean recommended for aggregation of local priorities in AHP.

摘要

•The results of aggregation by weighted arithmetic mean are normalization-dependent.•Weighted arithmetic mean aggregation fails to reflect preference information well.•Serious problems caused by the arithmetic mean aggregation shown on examples.•Theorems claiming the superiority of geometric mean aggregation in AHP presented.•Weighted geometric mean recommended for aggregation of local priorities in AHP.

论文关键词：Analytic hierarchy process,Aggregation,Weighted geometric mean,Weighted arithmetic mean,Rank reversal,Normalization of priorities

论文评审过程：Received 10 April 2018, Revised 22 June 2018, Accepted 23 June 2018, Available online 17 July 2018, Version of Record 27 July 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.06.060