[A novel improved TOPSIS method and its application in medical science]

Area of Science:

• Decision Sciences
• Operations Research
• Applied Mathematics

Context:

• The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is a widely used static comprehensive evaluation method.
• Traditional TOPSIS faces challenges like the reverse order problem and limited distinction in merit ranking.
• Existing evaluation values lack clarity on the degree of closeness to the ideal optimal solution.

Purpose:

• To propose an improved TOPSIS method that overcomes the limitations of the traditional approach.
• To enhance the sensitivity and isotonicity of the evaluation process.
• To introduce a novel method for more accurate comprehensive evaluations.

Summary:

• A new improved TOPSIS method is presented, demonstrating strict isotonicity and increased sensitivity compared to the traditional method.
• The enhanced evaluation value provides a clearer measure of closeness to the ideal optimal solution.
• The improved method effectively addresses the reverse order problem and enhances merit ranking distinctions.

Impact:

• Provides a more robust and accurate decision-making tool for comprehensive evaluations.
• Offers potential for improved applications in various fields, including medical evaluations.
• Enhances the reliability and discriminative power of multi-criteria decision-making methods.