My goal is to write a program that automatically selects a routing out of multiple proposed options.
The data consists out of the multiple proposed options with each the attributes time, costs and if there is a transhipment and also which of the options was selected.
Example of data:
My idea at the moment is that I have to apply so type of inference to learn which attribute (time, costs, transhipment) has the highest impact on how to choose the best option. But I don't know exactly where to start with this.
Is there a "best" ML algorithm for this? Or how should I approach this?
The dataset currently consists out of 1000 samples in case if this is important.
Thanks in advance for your responses.