Comparison Matrix In Analytic Hierarchy Process Research Articles

Repairing the Inconsistent Fuzzy Preference Matrix Using Multiobjective PSO

This paper presents a method using multiobjective particle swarm optimization (PSO) approach to improve the consistency matrix in analytic hierarchy process (AHP), called PSOMOF. The purpose of this method is to optimize two objectives which conflict each other, while improving the consistency matrix. They are minimizing consistent ratio (CR) and deviation matrix. This study focuses on fuzzy preference matrix as one model comparison matrix in AHP. Some inconsistent matrices are repaired successfully to be consistent by this method. This proposed method offers some alternative consistent matrices as solutions.

Improved AHP Method and Its Application in Risk Identification

The analytic hierarchy process (AHP) approach has been widely used in multicriteria decision making (MCDM). It is very difficult to meet the consistency requirement of a comparison matrix (CM) in AHP. The authors analyze the reasons for inconsistent CM in AHP and propose an improved AHP (IAHP) to improve CM consistency by using a sorting and ranking methodology. The results of comparing AHP with IAHP by MATLAB simulation show that IAHP is more suitable for solving MCDM problems when the number of elements or factors is 5 or more in MCDM. A case study is presented to illustrate the performance of IAHP when applied to risk iden- tification during an open-cut subway construction. The application results show that IAHP is superior to AHP in terms of CM consistency, information extraction effectiveness, and convenience in practical implementation. DOI: 10.1061/(ASCE)CO.1943-7862.0000605. © 2013 American Society of Civil Engineers. CE Database subject headings: Risk management; Construction management; Statistics. Author keywords: Risk identification; Analytic hierarchy process (AHP); Improved analytic hierarchy process; Construction management; Quantitative analysis; Statistical analysis.