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11 months ago in Decision Science , Operations Research By Pavitra

What’s a good decision-making method when you have many criteria and sub-criteria?

If I’m working with around six main criteria, each broken down into several sub-criteria, what decision-making method works best without getting messy?

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All Answers (2 Answers In All)

By Akash Answered 10 months ago

For this kind of structured complexity, the Analytic Hierarchy Process (AHP) is usually a solid choice. It lets you compare criteria and sub-criteria step by step, helping you assign sensible weights while checking for consistency. If you prefer a more economics-style approach, Multi-Attribute Utility Theory (MAUT) also works well, especially when you can quantify preferences. Both methods handle layered criteria cleanly and are widely used in practice.

Replied 10 months ago

By Pavitra

Thank you, that’s really helpful! I like that AHP allows step-by-step comparisons—it seems easier to manage than trying to weigh everything all at once.

By Amrit Singh Answered 9 months ago

Another approach you might consider is the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). It works well when you can define ideal and anti-ideal solutions for each criterion. TOPSIS ranks alternatives based on their distance to these reference points, which makes it intuitive when you want a clear “best option” among many. It’s particularly useful if your criteria are measurable and you want a fast computational method.

Replied 9 months ago

By Pavitra

Thank you so much for your response.

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