Multiplicity of Approach and Method in Augmentation of Simplex Method: A Review

Nor Asmaa Alyaa Nor Azlan, Effendi Mohamad*, Mohd Rizal Salleh, Oyong Novareza, Dani Yuniawan, Muhamad Arfauz A. Rahman, Adi Saptari, Mohd Amri Sulaiman

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

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The purpose of this review paper is to set an augmentation approach and exemplify distribution of augmentation works in Simplex method. The augmentation approach is classified into three forms whereby it comprises addition, substitution and integration. From the diversity study, the result shows that substitution approach appeared to be the highest usage frequency, which is about 45.2% from the total of percentage. This is then followed by addition approach which makes up 32.3% of usage frequency and integration approach for about 22.6% of usage frequency which makes it the least percentage of the overall usage frequency approach. Since it is being the least usage percentage, the paper is then interested to foresee a future study of integration approach that can be performed from the executed distribution of the augmentation works according to Simplex’s computation stages. A theme screening is then conducted with a set of criteria and themes to come out with a proposal of new integration approach of augmentation of Simplex method.

Original languageEnglish
Pages (from-to)53-60
Number of pages8
JournalMathematics and Statistics
Issue number1
Publication statusPublished - 01 Jan 2020
Externally publishedYes

Bibliographical note

Funding Information:
The authors would like to thank the Malaysian Government, Universiti Teknikal Malaysia Melaka (UTeM) and Fakulti Kejuruteraan Pembuatan for their support and cooperation.

Publisher Copyright:
© 2020 by authors, all rights reserved.

Copyright 2020 Elsevier B.V., All rights reserved.


  • Augmentation of Simplex Method
  • Multiplicity of Approach
  • Simplex Method

ASJC Scopus subject areas

  • Statistics and Probability
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty


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