Dear all,
I'm currently working on the optimization of the daily activity chain by using the GA algorithm. I developed a utility function consisting of (10) variables and their weights as follows:
U=v1w1+v2w2+........+v10w10.
The numerical values of the variables can be obtained from different sources, but the weight of each variable is based on the user's preferences. What's the best way to represent these weights: sensitive or scenarios analysis?
I would combine the two analyses to create a new method, that you can actually include in your study. The Ali Jamal Mahdi Sensitivity-Scenario Method :)
The sensitivity analysis is better. You can study the sensitivity of the output with respect to the chosen weights using any of the sensitivity analysis methods. In my opinion, one of the most powerful methods is the Non-Intrusive Polynomial Chaos Expansion method (PCE). It is a stochastic method which will show the direct sensitivity of the output to each input parameter and the nonlinear interaction of the input parameters and there effect on the output. You can check the following papers if you want more details:
1) Spatial Variation in Sensitivity of Hurricane Surge Characteristics to Hurricane Parameters
2) Multi-physics modelling andsensitivity analysis of olympic rowing boat dynamics
Let me know if you don't have access to the papers.
Dear Mahmoud Ayyad , thank you so much for the instructive answer. Actually I got the second paper, but I already request the first one.
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