Ranking Models for Decisions that Allow Attribute Trade-offs – SAW and TOPSIS
In Ranking Models for Decisions that Allow Attribute Trade-offs – SAW and TOPSIS, you'll learn ...
- Multiple Criteria Decision Making (MCDM) problems
- Compensatory decision models
- The construction of the decision matrix
- The theory behind SAW
Overview
In corporate or government decision making, there typically are a number of attributes or characteristics associated with the alternatives that are presented for a decision. In many circumstances, these alternatives need to be screened or ranked. There are a number of different approaches and methods that can be used to capture the decision environment and provide structure to the decision-making process.
This course addresses decision making circumstances where the decision-maker is permitted to trade-off attribute values. In these models, changes in one attribute or the weighting associated with that attribute can be offset with changes in any other attribute. With models such as these, a single number is usually assigned to each multidimensional characterization representing an alternative.
This course will address two of these methods, the Simple Additive Weighting (SAW) method and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method. Both of these methods are widely used in industry and the government. Both the theory and application of these methods will be addressed in this course.
Specific Knowledge or Skill Obtained
This course teaches the following specific knowledge and skills:
- Learn to apply the SAW method
- Under the theory behind TOPSIS
- Learn to apply the TOPSIS method
- Understand a comparison of the ranking of the methods presented
Certificate of Completion
You will be able to immediately print a certificate of completion after passing a multiple-choice quiz consisting of 10 questions. PDH credits are not awarded until the course is completed and quiz is passed.
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