Published June 1, 2025 | Version v1
Journal article Open

A New Approach to Weight Allocation in Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) for Fair Decision Making

  • 1. Department of Informatics Engineering, Sekolah Tinggi Teknologi Dumai, Indonesia

Description

This study proposes a new approach in weight allocation on the MOORA method to support fair and objective decision-making. MOORA modification using variation values is an approach that integrates variation values into the decision-making process using the MOORA method. the variation value is used to take into account the distribution of data in each criterion, so that it can increase the sensitivity of the analysis to the differences between alternatives. The MOORA modification with this variation value is named multi-objective optimization by ratio analysis-variance (MOORA-V). The results of the implementation show that this approach results in a more stable and reliable alternative ranking, even in the face of changes in weights or fluctuations in the data. Further sensitivity analysis confirmed that this method has good robustness and can reduce reliance on biased decisions. Thus, this new approach offers a more equitable and adaptive solution in multi-criteria decision-making, opening up opportunities for further development in more efficient and effective decision support systems. Further research can be developed to address uncertain data, such as fuzzy or interval data, to increase its flexibility in handling uncertainty in decision-making, as well as computational implementation using Python to improve reproducibility, facilitate validation by other researchers, and expand the potential for application in various fields.

Notes

Published in Evergreen, Volume 12, Issue 02. Citation formats available via DOI link.

Files

p1226-1237.pdf

Files (993.5 kB)

Name Size Download all
md5:bad0f33e6616f59c076664c7133c0cba
993.5 kB Preview Download

Additional details

Related works

Is identical to
Journal article: 10.5109/7363506 (DOI)
Is supplemented by
Other: https://citation.crossref.org/?doi=10.5109/7363506 (URL)