Dear Community
There are plenty of threads on the difference, but I always struggle when they are going towards a concrete example. I gave the one below here: https://www.researchgate.net/post/MCDM_vs_MADM_vs_MODM_vs_MAUT but the thread most likely is dead and I thought it might deserve a question on its own.
Whenever I try to explain it on a concrete example, I end up MADM confusing MODM. Could you help me on checking the example here? You want a new bicycle (instead of a car). As I would understand it, you could apply both methodologies on this question, but the approach is just slightly different.
MODM: You have 2 objectives: The bicycle should be light and it should have many gears
MADM: You go to the bike shop at write down the weight and the number of gears for each bike.
Bottom line: In MADM you end up knowing which bike you like most (ranking approach) and in MODM you end up knowing what bike you would need to build (design approach).
I will try to explain by one example. Suppose you want to maximize some function of two variables, say f(x1,x2). In your example, it is total utility. The permissible values of x1 and x2 are, say 0 to 10 for x1 and 0 to 15 for x2. (Only integer values for easy explanation). The only restriction on x1 and x2 is their sum should not exceed 12. Some of the possible solutions are (0,12), (1,11), (2,10) etc. At the same time the possible alternatives available in market are, say only 3. As an example, consider (3,9), (5,7) and (6,6). The difference will now be as follows: MADM checks only the three possible available solutions, while MODM checks all possible solutions, i.e. all 13 solutions.
Now imagine the case when x1 and x2 are allowed to take real values also. Moreover, the number of constraints may also be more than one. Then there are infinitely many possible solutions. In design approach, we try to find an optimal solution among these infinite solutions. Whereas in ranking approach, we just find the best solution among the given alternatives only (assuming that all the alternatives are such that they satisfy our requirements expressed in terms of constraints). If some alternative do not satisfy our requirement, then it can be rejected before starting the ranking process.
In this sense, MADM is a particular case of MODM where we are given only finite solutions among the possibly infinite solutions. I hope this discussion might have solved your doubt.
https://www.researchgate.net/publication/285536782_Optimization_Techniques_for_Engineers_Multi_Criteria_Decision_Making_%28MCDM%29_Lecture_13?ev=prf_pub
Presentation Optimization Techniques for Engineers Multi Criteria Decisio...
Many thanks for the answer. I didn't find any explanation on MODM in Alireza's slides, but they are interesting examples of a MADM In this respect.
Considering explanations from Rajesh, I think the example I gave is quite correct. So in MODA you need to have goals that load to the same attribute, isn't It?
Yes, the objective is same, but the number of alternatives differ. However, multi-objective optimization has its own independent theory also. There is a special book written on this topic by Kalyanmoy Deb. The homepage of the book is
http://as.wiley.com/WileyCDA/WileyTitle/productCd-047187339X.html
MCDM encompasses both MCDA and MODM.
MCDA relates to a number of discrete alternatives.
MODM relates to an infinite or uncountable number of alternatives.
Ricardo mateus just included MCDA to the mix, but doesn´t calarify MADM. Now me have MCDM, MCDA, MADM, MODM.
I have to admit the more answers I read the less consensus I find.
Jaime, you are right, Ricardo did not explain what MCDA stands for and did not relate it to MADM.
I came yesterday to read my example from back then again. The question of weighting utilities in MODM still remains, but else I think the comparison holds true.
True, I just find it frustrating as I have to choose a method but so many papers so many content but the basics are kind of floating. Which keeps me from getting a good grip.
Jaime, I can recommend the following reading: Malczewski J. (1999): GIS and Multicriteria Decision Analysis. John Wiley & Sons Inc.
(not the updated version). Well written, straight forward textbook, clear graphics and helpful even for non-GIScientists.
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