Are there any differences between weighted sum model (WSM) method & simple additive weighting (SAW) method in multi-criteria decision analysis (MCDA)?
Dear Ali,
Yes, it is the same model. Be careful about its properties though, mainly those of incomparability across attributes' units (e.g. adding "apples" and "oranges" - hence, normalization/standardization is probably needed, unless you are adding attributes of the same unit) or compensation between attributes (e.g. proportionate to the ratio of their weights).
You can have a look at Section 2.2.1 of this book (but also more or less any MCDA theory-related book) for more:
Triantaphyllou, E. (2000). Multi-criteria decision making methods. In Multi-criteria decision making methods: A comparative study (pp. 5-21). Springer, Boston, MA. URL: Book Multi-Criteria Decision Making Methods
All the best,
Menelaos
Hello Ali Reza Shahvaran
Menelaos Tasiou already answered your question but I endorse his answer: WSM and SAW are the same. It's also known as "additive aggregation model".
The components of the model we costumarily call by "weights" are better defined as "scaling constants" since they work not to define an order of importance of the criteria but a rate of compensation between them.
Hope it can help you.
Regards,
Victor
In weighting sum models the values of the weights are chosen to differentiate between the importance of each objective.However in the weighting method which is used to scalarize the multiobjective problems,the values of the weights does not indicate the importance of the different objectives .
Dear Menelaos Tasiou ,
Thank you very much for your answer. I will study the book.
Regards,
Ali Reza Shahvaran
Dear Victor Diogho Heuer de Carvalho ,
Thank you for your informative reply.
Regards,
Ali Reza Shahvaran
Dear Dr. M. Osman ,
I am grateful with your help.
Regards,
Ali Reza Shahvaran
This is all nonsense. The weights do not relate to importance of an objective. You need to do the math.
There are many differences in the determination of weights in the WSM method, almost all are wrong. The weights do not represent importance, they define an indifference surface.