An improvement model of analytic hierarchy process based on genetic algorithm

Xin Sun*, Jun Zheng, Yin Pang, Chengfeng Ye, Lei Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The analytic hierarchy process (AHP) is widely used in many fields as a classical multi attribute decision-making approach. Judgment matrix consistency is the core problem in the AHP. A nonlinear programming model is proposed for improving the consistency of the judgment matrix. Then a genetic algorithm is designed to solve the nonlinear programming model to determine matrix consistency adjustments. And the validity and feasibility of this method is validated by an example.

Original languageEnglish
Title of host publicationHigh Performance Networking, Computing, and Communication Systems - Second International Conference, ICHCC 2011, Selected Papers
Pages237-244
Number of pages8
DOIs
Publication statusPublished - 2011
Event2011 2nd International Conference on High-Performance Networking, Computing and Communications Systems, ICHCC 2011 - Singapore, Singapore
Duration: 5 May 20116 May 2011

Publication series

NameCommunications in Computer and Information Science
Volume163 CCIS
ISSN (Print)1865-0929

Conference

Conference2011 2nd International Conference on High-Performance Networking, Computing and Communications Systems, ICHCC 2011
Country/TerritorySingapore
CitySingapore
Period5/05/116/05/11

Keywords

  • analytic hierarchy process (AHP)
  • genetic algorithm
  • judgment matrix

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