Evolving Systems

, Volume 9, Issue 2, pp 169–180 | Cite as

Modality of teaching learning based optimization algorithm to reduce the consistency ratio of the pair-wise comparison matrix in analytical hierarchy processing

  • Prashant BorkarEmail author
  • M. V. Sarode
Original Paper


This paper presents an approach to improve the consistency of pair-wise comparison matrix in analytical hierarchy process (AHP) using teaching learning based optimization (TLBO) algorithm. The purpose of this proposed approach to minimize the consistency ratio (CR). Consistency test for the comparison matrix in AHP have been studied rigorously since AHP was introduced in 1970s. However, existing approaches are either too complicated or difficult. Most of them could not preserve the original judgments provided by an expert. To improve the consistency ratio (CR), this research work proposes a simple, effective and efficient method which will minimize the CR to almost zero while preserving the judgment values in pair-wise comparison matrix. The correctness of the proposed method is proved by applying it to two real world case studies reported in literature, namely new product design selection and material selection (work tool combination). The experimentation shows that the proposed approach is efficient and accurate to satisfy the consistency requirements of AHP.


Analytical hierarchy process (AHP) Pair-wise comparison matrix Teaching learning based optimization (TLBO) Consistency ratio 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringGHRCENagpurIndia
  2. 2.Department of Computer Science and EngineeringGovernment Polytechnic YawatmalYawatmalIndia

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