A simulation based comparative study of normalization procedures in multiattribute decision making

Subrata Chakraborty · Chung‐Hsing Yeh

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Multi-Criteria Decision Making Decision Support System Applications Optimization and Mathematical Programming

Abstract

Abstract: – Normalization procedures are required in multiattribute decision making (MADM) to transform performance ratings with different data measurement units in a decision matrix into a compatible unit. MADM methods generally use one particular normalization procedure without considering the suitability of other available procedures. This study compares four commonly known normalization procedures in terms of their ranking consistency and overall preference value consistency when used with the most widely used simple additive weight method. To achieve this, new performance measure indices are introduced and new simulation settings are devised for dealing with various measurement settings. A wide range of MADM problems with various measurement scales are generated by simulation for the comparison study. The experiment result shows that vector normalization and linear scale transformation (the max method) outperforms other normalization procedures when used with SAW.

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References

1985The Analytic Hierarchy Process 1977A scaling method for priorities in hierarchical structures 1981Multiple Attribute Decision Making: Methods and Applications 1994How to Make a Decision: The Analytic Hierarchy Process 1995Multiple attribute decision making : an introduction 1977How to Use Multiattribute Utility Measurement for Social Decisionmaking 1998Multi-attribute decision making: A simulation comparison of select methods 1954An Approximate Measure of Value

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