Selecting Normalization Techniques for the Analytical Hierarchy Process

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

1 Citation (Scopus)

Abstract

One of the matters which has influence on Multi-Criteria Decision Making (MCDM) methods is the normalizing procedure. Most MCDM methods implement normalization techniques to produce dimensionless data in order to aggregate/rank alternatives. Using different normalization techniques may lead to different rankings. So, selecting a more suitable normalization technique is a requirement in the decision process. Specially, by the advent of big data and its role in developing life’s quality, finding the best normalization technique in MCDM models are more challenging. Collecting data from sensors causes more complex decision problems, thus, providing accurate normalized values (in the same unit) is more critical in these types of contexts. In this research, we analyze and evaluate the effect of different normalization techniques on the ranking of alternatives in one of the Multi-Criteria Decision Making (MCDM) methods called Analytical Hierarchy Process (AHP) using our developed assessment framework. An illustrative example (smart car parking) is used to discuss the suitability of the framework and recommend more proper normalization technique for AHP. Furthermore, the developing of technological innovation is expected by using the evaluation framework which can raise the accuracy of the normalized values in decision problems.

Original languageEnglish
Title of host publicationTechnological Innovation for Life Improvement - 11th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020, Proceedings
EditorsLuis M. Camarinha-Matos, Nastaran Farhadi, Fábio Lopes, Helena Pereira
Place of PublicationCham
PublisherSpringer
Pages43-52
Number of pages10
ISBN (Electronic)978-3-030-45124-0
ISBN (Print)978-3-030-45123-3
DOIs
Publication statusPublished - 2020
Event11th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020 - Costa de Caparica, Portugal
Duration: 1 Jul 20203 Jul 2020

Publication series

NameIFIP Advances in Information and Communication Technology
PublisherSpringer
Volume577
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

Conference11th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020
CountryPortugal
CityCosta de Caparica
Period1/07/203/07/20

Keywords

  • Aggregation
  • AHP
  • Big data
  • Data fusion
  • Decision Making
  • MCDM
  • Normalization

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