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:: Volume 17, Issue 1 (5-2026) ::
IJOR 2026, 17(1): 1-19 Back to browse issues page
A New Decision- Making Method Based on Shannon Entropy Analysis
Hamid Babei Meybodi , Shabnam Mohammadi Ardakani * , Hossein Ghaneai
Department of Management , Yazd University, Yazd, , Iran , sh.mohammadi@stu.yazd.ac.ir
Abstract:   (131 Views)
Effective management, as one of the central pillars of organizational success, hinges on the ability to make informed decisions by appropriately combining and coordinating various elements to achieve desired objectives. In decision-making processes, especially in complex scenarios, decision-makers often rely on a multitude of factors to arrive at the most suitable conclusion. This is particularly true in multi-criteria decision-making (MCDM), where decisions are based on evaluating several criteria rather than a single measure of optimality. The growing body of research over recent decades has delved deeply into MCDM methodologies, yet one fundamental aspect remains: the varying significance of the criteria involved. It is critical to accurately determine the weight or importance of each criterion to ensure optimal decision outcomes.
In this paper, we introduce a novel weighting technique designed to address the challenges of assigning weights in MCDM problems, called the Dispersion-based Weighting Method (DWM). This method builds upon the principles of statistical dispersion and offers an efficient alternative to traditional entropy-based weighting methods. The process involves constructing a criterion matrix, followed by the calculation of the mean, standard deviation, and coefficient of variation for each criterion. The weights are then computed based on these statistical measures, providing a robust and straightforward approach for determining the relative importance of each criterion.
To validate the proposed DWM technique, several numerical examples are presented, demonstrating its practical application and effectiveness. Additionally, we compare the results obtained using DWM with those derived from the well-established Shannon entropy method, which is widely used in MCDM applications. The comparative analysis reveals a strong correlation between the two techniques, while highlighting the advantages of the DWM approach, including:
  • Reduced computational complexity
  • No requirement for data normalization
  • Applicability to both positive and negative data sets
The findings suggest that DWM offers a more accessible, efficient, and versatile alternative to traditional methods, particularly in situations where computational efficiency and handling of diverse data types are crucial.
 
Keywords: Multiple Criteria Decision Making (MCDM), Multi-Objective Decision Making (MODM), Multi-Attribute Decision Making (MADM), Dispersion-based Weighting Method (DWM), Shannon Entropy
Full-Text [PDF 810 kb]   (290 Downloads)    
Type of Study: Original | Subject: Other
Received: 2026/02/23 | Accepted: 2026/05/8 | Published: 2026/05/8
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 17, Issue 1 (5-2026) Back to browse issues page
مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
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