A Generic Approach for Weight Assignment to the Decision Making Parameters

Weight assignment to the decision parameters is a crucial factor in the decision-making process. Any imprecision in weight assignment to the decision attributes may lead the whole decision-making process useless which ultimately mislead the decision-makers to find an optimal solution. Therefore, attributes’ weight allocation process should be flawless and rational, and should not be just assigning some random values to the attributes without a proper analysis of the attributes’ impact on the decision-making process. Unfortunately, there is no sophisticated mathematical framework for analyzing the attribute’s impact on the decision-making process and thus the weight allocation task is accomplished based on some human sensing factors. To fill this gap, present paper proposes a weight assignment framework that analyzes the impact of an attribute on the decision-making process and based on that, each attribute is evaluated with a justified numerical value. The proposed framework analyzes historical data to assess the importance of an attribute and organizes the decision problems in a hierarchical structure and uses different mathematical formulas to explicit weights at different levels. Weights of mid and higher-level attributes are calculated based on the weights of root-level attributes. The proposed methodology has been validated with diverse data. In addition, the paper presents some potential applications of the proposed weight allocation scheme.

@article{Hasan2019,
  title     = {A Generic Approach for Weight Assignment to the Decision Making Parameters},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {11},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Md Zahid Hasan and Shakhawat Hossain and Mohammad Shorif Uddin and Mohammad Shahidul Islam},
  doi       = {10.14569/IJACSA.2019.0101170},
  url       = {https://doi.org/10.14569/IJACSA.2019.0101170}
}