ymrodriguez / sortlot-tfg Goto Github PK

Se va a hacer en la función isBetterPP

Pesos adaptables según unas características como el peso medio de los paquetes

This issue is important because it refines the optimization algorithm. The approach is:

1. Determine all the parameters to optimize.
2. Create a global fitness function depending on the final result of a packing process (i.e. Volume Occupied combined with unloading obstacles a global estimation of how secure is the solution depending on the average of supported area, etc)
3. Optimize the value of these parameters with a specific optimisation strategy.
4. Apply the optimisation in different scenarios and estimate the best global value.

In a few situations, since the step by step packing is calculated using euclidean distance, there are packets that appear to be in the space without the packets that bear them.

It will better for the visualization. Add it on the solution dataset, not during computing

Right know it is fixed to 20 cm but it should change, depending on the smallest dimension present in the dataset.

Currently we handle the insertion id but its the id by the algo not by an operator

Posiblemente incorporando alguna biblioteca como Numba o Cython