A decision-making model with sequential incomplete additive pairwise comparisons

作者：

Highlights：

• A sequential model of incomplete additive pairwise comparisons is proposed.

• The particle swarm optimization is used to estimate missing values in an incomplete matrix.

• A novel algorithm is reported to improve additive consistency of an additive comparison matrix.

• A new decision-making model with incomplete additive reciprocal matrices is offered.

摘要

•A sequential model of incomplete additive pairwise comparisons is proposed.•The particle swarm optimization is used to estimate missing values in an incomplete matrix.•A novel algorithm is reported to improve additive consistency of an additive comparison matrix.•A new decision-making model with incomplete additive reciprocal matrices is offered.

论文关键词：Decision making,Sequential model,Incomplete additive pairwise comparison,Particle swarm optimization (PSO),Granularity-based method

论文评审过程：Received 22 September 2021, Revised 9 November 2021, Accepted 14 November 2021, Available online 27 November 2021, Version of Record 2 December 2021.

论文官网地址：https://doi.org/10.1016/j.knosys.2021.107766