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What are the best ways to aggregate criteria weights and judgments in multi-criteria decision making?

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Multi-criteria decision making (MCDM) is a branch of operations research that helps you choose the best option among several alternatives based on multiple criteria. However, to do that, you need to assign weights to each criterion and compare the alternatives based on their performance on each criterion. How do you aggregate these weights and judgments in a consistent and reliable way? In this article, you will learn about some of the best methods to do so.

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1 Weighting methods

One of the first steps in MCDM is to determine the relative importance of each criterion. There are many methods to do this, such as direct rating, pairwise comparison, rank order, swing weighting, and analytic hierarchy process (AHP). Each method has its own advantages and disadvantages, depending on the type and number of criteria, the availability and quality of data, and the preferences and judgments of the decision makers. You should choose a method that is easy to understand, apply, and communicate, and that reflects the true priorities of the decision problem.

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Dr. Michael Gendron

It’s all about workforce development and a great education. Do what makes you happy!
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Direct rating is perhaps the easiest to explain. However, I’ve use that as a first cut technique. Looking at more expansive decision-making I prefer AHP.

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2 Judgment methods

Once you have the weights of each criterion, you need to evaluate how each alternative performs on each criterion. This can be done using quantitative or qualitative data, or a combination of both. Some of the methods to do this are scoring, rating, ranking, outranking, and goal programming. Each method has its own logic and assumptions, and may produce different results for the same problem. You should choose a method that is consistent with the nature and scale of the data, and that captures the trade-offs and synergies among the criteria.

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3 Aggregation methods

After you have the weights and judgments for each criterion and alternative, you need to combine them into a single score or ranking for each alternative. This can be done using different aggregation methods, such as weighted sum, weighted product, ordered weighted averaging (OWA), or technique for order preference by similarity to ideal solution (TOPSIS). Each method has its own properties and implications, and may favor different types of alternatives. You should choose a method that is compatible with the weighting and judgment methods, and that reflects the decision context and objectives.

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Dr. Michael Gendron

It’s all about workforce development and a great education. Do what makes you happy!
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I agree, my only caveat is that you have to understand the audience. If the stakeholder audience is sophisticated enough to understand some of these more elaborate techniques, then fine, but if not. I would stick to the basics.

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4 Sensitivity analysis

One of the challenges of MCDM is that the results may depend on the choices and uncertainties of the decision makers. Therefore, it is important to perform sensitivity analysis to check how robust the results are to changes in the weights, judgments, or aggregation methods. Sensitivity analysis can help you identify the key factors that influence the outcome, the range of possible outcomes, and the scenarios that lead to different outcomes. You should use sensitivity analysis to validate, improve, and communicate your decision.

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5 Decision support tools

To help you apply the various methods of MCDM, you can use some of the available decision support tools, such as software, spreadsheets, or online platforms. These tools can help you collect, process, and visualize the data, perform the calculations, and generate the results. Some of the examples of these tools are Expert Choice, Super Decisions, Decision Lens, 1000Minds, and MCDA Web. You should use these tools to simplify and enhance your decision making process.

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6 Best practices

To make the most of MCDM, you should adhere to certain best practices. These include defining the decision problem and objectives clearly and comprehensively, involving relevant stakeholders and experts in the process, selecting the appropriate criteria and alternatives, using reliable data sources and methods to obtain weights and judgments, contrasting different aggregation methods and results, performing sensitivity analysis to test the robustness of the results, interpreting and communicating the results in a transparent manner, and using the results to support your decision but not dictate it.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Dr. Michael Gendron

It’s all about workforce development and a great education. Do what makes you happy!
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I have found it is most important to understand the stakeholder group that would like the output from multi criteria decision making. It’s simple, if you can’t explain it in terms the stakeholders can understand then use something different.

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What are the best ways to aggregate criteria weights and judgments in multi-criteria decision making?

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3

4

5

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7

1 Weighting methods

2 Judgment methods

3 Aggregation methods

4 Sensitivity analysis

5 Decision support tools

6 Best practices

7 Here’s what else to consider

Operations Research

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What are the best ways to aggregate criteria weights and judgments in multi-criteria decision making?

1

2

3

4

5

6

7

1 Weighting methods

2 Judgment methods

3 Aggregation methods

4 Sensitivity analysis

5 Decision support tools

6 Best practices

7 Here’s what else to consider

Operations Research

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