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3 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?

DecisionMaking

All Answers (2 Answers In All)

By Akash Answered 2 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 1 month 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 1 month 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 1 month ago

By Pavitra

Thank you so much for your response.

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