Best-Worst Multi-Criteria Decision-Making Method

Author: Jafar Rezaei
Faculty of Technology, Policy and Management
Delft University of Technology

Decision-making is part of our daily life. We have to choose. Choosing is difficult. For some decision-making problems, we have standard measures (or tools), for some we don’t. Travel ‘time’ is used to choose the fastest transportation mode from Amsterdam to Lisbon. ‘Time’ is a physical quantity that can be measured. We measure the flight time through comparing the time between Amsterdam to Lisbon to an hour which has already been a standard. All of us can use the same ‘International System of Units’ (SI) for the measurements we need for our decision-making problems, when we are dealing with physical quantities like time, mass, and length. But how should we measure something like ‘kindness’, which is not a physical quantity and for which there is not standard? How about beauty, equity, justice, etc. Can we use comparison to measure such concepts as well? The answer is yes. Although in such situations we don’t have standards, we can still compare alternatives  with respect to these concepts (e.g. comparing people with respect to their kindness). Although in some situations, we make a decision based on a single or multiple physical quantities, in most decision-making problems, we have to choose our best alternative considering multiple measures (criteria), some of which are physical, some are not. Such problems are called multi-criteria decision-making (MCDM) problems. These are complex problems, for which we need efficient and effective tools. One of the most well-known and effective ways to formulate and solve the problem is ‘pairwise comparison’; a method which has become a solid basis for some MCDM methods during the last decades. One of the most efficient MCDM methods, which is comparison-based, is Best-Worst Method (BWM). This method gives a logical structure to the pairwise comparisons, and uses some simple mathematical models to help the decision-maker (DM) to choose his/her best alternative. That is, if a DM has to choose among m alternatives with respect to n criteria, the DM is first asked to identify the best (e.g. most desirable, most important), and the worst (e.g. least desirable, least important) criteria. He/she is then asked to compare the best to the other criteria, and also the other criteria to the worst. These pairwise comparisons are used as the input of some mathematical models, which derive the relative importance (weights) of these criteria. This procedure is repeated n times for the alternatives, each time with respect to one criterion. Finally through the multiplication of the weights of the criteria by the weights of the alternatives with respect to the criteria we come up with a final global score for each alternative which shows the desirability of that alterative compared to the other alternatives. The DM can then choose his/her best alternative. To read the paper please click here, and for more information about this method and different applications please visit

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